R Installation and Administration

Permission is granted to make and distribute verbatim copies of this
manual provided the copyright notice and this permission notice are
preserved on all copies.

Permission is granted to copy and distribute modified versions of this
manual under the conditions for verbatim copying, provided that the
entire resulting derived work is distributed under the terms of a
permission notice identical to this one.

Permission is granted to copy and distribute translations of this manual
into another language, under the above conditions for modified versions,
except that this permission notice may be stated in a translation
approved by the R Core Team.

1.1 Getting and unpacking the sources

The simplest way is to download the most recent
R-x.y.z.tar.gz file, and unpack it with

tar -xf R-x.y.z.tar.gz

on systems that have a suitable1tar installed. On other systems you need to
have the gzip program installed, when you can use

gzip -dc R-x.y.z.tar.gz | tar -xf -

The pathname of the directory into which the sources are unpacked should
not contain spaces, as most make programs (and specifically
GNUmake) do not expect spaces.

If you want the build to be usable by a group of users, set umask
before unpacking so that the files will be readable by the target group
(e.g., umask 022 to be usable by all users). Keep this
setting of umask whilst building and installing.

If you use a recent GNU version of tar and do this
as a root account (which on Windows includes accounts with administrator
privileges) you may see many warnings about changing ownership. In
which case you can use

tar --no-same-owner -xf R-x.y.z.tar.gz

and perhaps also include the option --no-same-permissions.
(These options can also be set in the TAR_OPTIONS environment
variable: if more than one option is included they should be separated
by spaces.)

1.2 Getting patched and development versions

A patched version of the current release, ‘r-patched’, and the
current development version, ‘r-devel’, are available as daily
tarballs and via access to the R Subversion repository. (For the two
weeks prior to the release of a minor (3.x.0) version, ‘r-patched’
tarballs may refer to beta/release candidates of the upcoming release,
the patched version of the current release being available via
Subversion.)

The tarballs are available from
ftp://ftp.stat.math.ethz.ch/pub/Software/R/. Download
R-patched.tar.gz or R-devel.tar.gz (or the .tar.bz2
versions) and unpack as described in the previous section. They are
built in exactly the same way as distributions of R releases.

to check out ‘r-devel’ into directory path (which will be
created if necessary). The alpha, beta and RC versions of an upcoming
x.y.0 release are available from
‘https://svn.r-project.org/R/branches/R-x-y-branch/’ in
the four-week period prior to the release.

Note that ‘https:’ is required2,
and that the SSL certificate for the Subversion server of the R project
should be recognized as from a trusted source.

Note that retrieving the sources by e.g. wget -r or
svn export from that URL will not work (and will give a error
early in the make process): the Subversion information is
needed to build R.

The Subversion repository does not contain the current sources for the
recommended packages, which can be obtained by rsync or
downloaded from CRAN. To use rsync to install the
appropriate sources for the recommended packages, run
./tools/rsync-recommended from the top-level directory of the
R sources.

If downloading manually from CRAN, do ensure that you have the
correct versions of the recommended packages: if the number in the file
VERSION is ‘x.y.z’ you need to download
the contents of ‘https://CRAN.R-project.org/src/contrib/dir’,
where dir is ‘x.y.z/Recommended’ for
r-devel or x.y-patched/Recommended for r-patched,
respectively, to directory src/library/Recommended in the sources
you have unpacked. After downloading manually you need to execute
tools/link-recommended from the top level of the sources to
make the requisite links in src/library/Recommended. A suitable
incantation from the top level of the R sources using wget
might be (for the correct value of dir)

2 Installing R under Unix-alikes

R will configure and build under most common Unix and Unix-alike
platforms including ‘cpu-*-linux-gnu’ for the
‘alpha’, ‘arm’, ‘hppa’, ‘ix86’,
‘m68k’, ‘mips’, ‘mipsel’, ‘powerpc’,
‘s390’, ‘sparc’, and ‘x86_64’ CPUs,
‘x86_64-apple-darwin’, ‘i386-sun-solaris’ and
‘sparc-sun-solaris’ as well as
perhaps (it is tested less frequently on these platforms)
‘i386-apple-darwin’, ‘i386-*-freebsd’, ‘x86_64-*-freebsd’,
‘i386-*-netbsd’, ‘i386-*-openbsd’ and
‘powerpc-ibm-aix6*’

In addition, binary distributions are available for some common Linux
distributions and for OS X (formerly Mac OS). See the FAQ for
current details. These are installed in platform-specific ways, so for
the rest of this chapter we consider only building from the sources.

Cross-building is not possible: installing R builds a minimal version
of R and then runs many R scripts to complete the build.

2.1 Simple compilation

First review the essential and useful tools and libraries in
Essential and useful other programs under a Unix-alike, and install
those you
want or need. Ensure that the environment variable TMPDIR is
either unset (and /tmp exists and can be written in and scripts
can be executed from) or points to the absolute path to a valid
temporary directory (one from which execution of scripts is allowed)
which does not contain spaces.3

Choose a directory to install the R tree (R is not just a binary, but
has additional data sets, help files, font metrics etc). Let us call
this place R_HOME. Untar the source code. This should create
directories src, doc, and several more under a top-level
directory: change to that top-level directory (At this point North
American readers should consult Setting paper size.) Issue the
following commands:

./configure
make

(See Using make if your make is not called ‘make’.) Users of
Debian-based 64-bit systems4 may need

./configure LIBnn=lib
make

Then check the built system works correctly by

make check

Failures are not necessarily problems as they might be caused by missing
functionality, but you should look carefully at any reported
discrepancies. (Some non-fatal errors are expected in locales that do
not support Latin-1, in particular in true C locales and
non-UTF-8 non-Western-European locales.) A failure in
tests/ok-errors.R may indicate inadequate resource limits
(see Running R).

More comprehensive testing can be done by

make check-devel

or

make check-all

see file tests/README and Testing a Unix-alike Installation
for the possibilities of doing this in parallel. Note that these checks
are only run completely if the recommended packages are installed.

If the command configure and make commands execute
successfully, a shell-script front-end called R will be created
and copied to R_HOME/bin. You can link or copy this script
to a place where users can invoke it, for example to
/usr/local/bin/R. You could also copy the man page R.1 to
a place where your man reader finds it, such as
/usr/local/man/man1. If you want to install the complete R
tree to, e.g., /usr/local/lib/R, see Installation. Note:
you do not need to install R: you can run it from where it was
built.

You do not necessarily have to build R in the top-level source
directory (say, TOP_SRCDIR). To build in
BUILDDIR, run

cd BUILDDIRTOP_SRCDIR/configure
make

and so on, as described further below. This has the advantage of always
keeping your source tree clean and is particularly recommended when you
work with a version of R from Subversion. (You may need
GNUmake to allow this, and you will need no spaces
in the path to the build directory. It is unlikely to work if the
source directory has previously been used for a build.)

Note: if you already have R installed, check that where you installed
R replaces or comes earlier in your path than the previous
installation. Some systems are set up to have /usr/bin (the
standard place for a system installation) ahead of /usr/local/bin
(the default place for installation of R) in their default path, and
some do not have /usr/local/bin on the default path.

2.2 Help options

By default HTML help pages are created when needed rather than being
built at install time.

If you need to disable the server and want HTML help, there is the
option to build HTML pages when packages are installed
(including those installed with R). This is enabled by the
configure option --enable-prebuilt-html. Whether
R CMD INSTALL (and hence install.packages) pre-builds
HTML pages is determined by looking at the R installation and is
reported by R CMD INSTALL --help: it can be overridden by
specifying one of the INSTALL options --html or
--no-html.

The server is disabled by setting the environment variable
R_DISABLE_HTTPD to a non-empty value, either before R is
started or within the R session before HTML help (including
help.start) is used. It is also possible that system security
measures will prevent the server from being started, for example if the
loopback interface has been disabled. See
?tools::startDynamicHelp for more details.

You will not be able to build any of these unless you have
texi2any version 5.1 or later installed, and for PDF you must
have texi2dvi and texinfo.tex installed (which are part
of the GNUtexinfo distribution but are, especially
texinfo.tex, often made part of the TeX package in
re-distributions). For historical reasons, the path to
texi2any can be set by macro ‘MAKEINFO’ in
config.site (makeinfo is nowadays a link to
texi2any).

The PDF versions can be viewed using any recent PDF viewer: they have
hyperlinks that can be followed. The info files are suitable for
reading online with Emacs or the standalone GNUinfo
program. The PDF versions will be created using the paper size selected
at configuration (default ISO a4): this can be overridden by setting
R_PAPERSIZE
on the make command line, or setting R_PAPERSIZE in the
environment and using make -e. (If re-making the manuals for
a different paper size, you should first delete the file
doc/manual/version.texi. The usual value for North America would
be ‘letter’.)

There are some issues with making the PDF reference manual,
fullrefman.pdf or refman.pdf. The help files contain both
ISO Latin1 characters (e.g. in text.Rd) and upright quotes,
neither of which are contained in the standard LaTeX Computer Modern
fonts. We have provided four alternatives:

times

(The default.) Using standard PostScript fonts, Times Roman, Helvetica
and Courier. This works well both for on-screen viewing and for
printing. One disadvantage is that the Usage and Examples sections may
come out rather wide: this can be overcome by using in addition
either of the options inconsolata (on a Unix-alike only if found
by configure) or beramono, which replace the Courier
monospaced font by Inconsolata or Bera Sans mono respectively. (You
will need a recent version of the appropriate LaTeX package
inconsolata5 or
bera installed.)

Note that in most LaTeX installations this will not actually use the
standard fonts for PDF, but rather embed the URW clones NimbusRom,
NimbusSans and (for Courier, if used) NimbusMon.

Using the Latin Modern fonts. These are not often installed as
part of a TeX distribution, but can obtained from
https://www.ctan.org/tex-archive/fonts/ps-type1/lm/ and
mirrors. This uses fonts rather similar to Computer Modern, but is not
so good on-screen as times.

cm-super

Using type-1 versions of the Computer Modern fonts by Vladimir Volovich.
This is a large installation, obtainable from
https://www.ctan.org/tex-archive/fonts/ps-type1/cm-super/
and its mirrors. These type-1 fonts have poor hinting and so are
nowhere near as readable on-screen as the other three options.

ae

A package to use composites of Computer Modern fonts. This works well
most of the time, and its PDF is more readable on-screen than the
previous two options. There are three fonts for which it will need to
use bitmapped fonts, tctt0900.600pk, tctt1000.600pk and
tcrm1000.600pk. Unfortunately, if those files are not available,
Acrobat Reader will substitute completely incorrect glyphs so you need
to examine the logs carefully.

The default can be overridden by setting the environment variable
R_RD4PDF. (On Unix-alikes, this will be picked up at install time
and stored in etc/Renviron, but can still be overridden when the
manuals are built, using make -e.) The usual6 default value for R_RD4PDF is
‘times,inconsolata,hyper’: omit ‘hyper’ if you do not want
hyperlinks (e.g. for printing the manual) or do not have LaTeX
package hyperref, and omit ‘inconsolata’ if you do not have
LaTeX package inconsolata installed.

Further options, e.g for hyperref, can be included in a file
Rd.cfg somewhere on your LaTeX search path. For example, if
you prefer the text and not the page number in the table of contents to
be hyperlinked use

\ifthenelse{\boolean{Rd@use@hyper}}{\hypersetup{linktoc=section}}{}

or

\ifthenelse{\boolean{Rd@use@hyper}}{\hypersetup{linktoc=all}}{}

to hyperlink both text and page number.

Ebook versions of most of the manuals in one or both of .epub and
.mobi formats can be made by running in doc/manual one of

make ebooks
make epub
make mobi

This requires ebook-convert from Calibre
(http://calibre-ebook.com/download), or from most Linux
distributions). If necessary the path to ebook-convert can be
set as make macro EBOOK to by editing doc/manual/Makefile
(which contains a commented value suitable for OS X).

2.4 Installation

To ensure that the installed tree is usable by the right group of users,
set umask appropriately (perhaps to ‘022’) before unpacking
the sources and throughout the build process.

After

./configure
make
make check

(or, when building outside the source,
TOP_SRCDIR/configure, etc) have been completed
successfully, you can install the complete R tree to your system by
typing

make install

A parallel make can be used (but run make before make
install). Those using GNU make 4.0 or later may want to use
make -j n -O to avoid interleaving of output.

This will install to the following directories:

prefix/bin or bindir

the front-end shell script and other scripts and executables

prefix/man/man1 or mandir/man1

the man page

prefix/LIBnn/R or libdir/R

all the rest (libraries, on-line help system, …). Here
LIBnn is usually ‘lib’, but may be ‘lib64’ on some
64-bit Linux systems. This is known as the R home directory.

where prefix is determined during configuration (typically
/usr/local) and can be set by running configure with
the option --prefix, as in

./configure --prefix=/where/you/want/R/to/go

where the value should be an absolute path. This causes make
install to install the R script to
/where/you/want/R/to/go/bin, and so on. The prefix of the
installation directories can be seen in the status message that is
displayed at the end of configure. The installation may need
to be done by the owner of prefix, often a root account.

You can install into another directory tree by using

make prefix=/path/to/here install

at least with GNUmake and current Solaris
make (but not some older Unix makes).

More precise control is available at configure time via options: see
configure --help for details. (However, most of the ‘Fine
tuning of the installation directories’ options are not used by R.)

Configure options --bindir and --mandir are supported
and govern where a copy of the R script and the man
page are installed.

The configure option --libdir controls where the main R
files are installed: the default is ‘eprefix/LIBnn’,
where eprefix is the prefix used for installing
architecture-dependent files, defaults to prefix, and can be set
via the configure option --exec-prefix.

Each of bindir, mandir and libdir can also be
specified on the make install command line (at least for
GNUmake).

The configure or make variables rdocdir and
rsharedir can be used to install the system-independent
doc and share directories to somewhere other than
libdir. The C header files can be installed to the value of
rincludedir: note that as the headers are not installed into a
subdirectory you probably want something like
rincludedir=/usr/local/include/R-3.2.1.

If you want the R home to be something other than
libdir/R, use rhome: for example

make install rhome=/usr/local/lib64/R-3.2.1

will use a version-specific R home on a non-Debian Linux 64-bit
system.

If you have made R as a shared/static library you can install it in
your system’s library directory by

make prefix=/path/to/here install-libR

where prefix is optional, and libdir will give more
precise control.7 However, you should not install
to a directory mentioned in LDPATHS (e.g.
/usr/local/lib64) if you intend to work with multiple versions of
R, since that directory may be given precedence over the lib
directory of other R installations.

make install-strip

will install stripped executables, and on platforms where this is
supported, stripped libraries in directories lib and
modules and in the standard packages.

Note that installing R into a directory whose path contains spaces is
not supported, and some aspects (such as installing source packages)
will not work.

To install info and PDF versions of the manuals, use one or both of

make install-info
make install-pdf

Once again, it is optional to specify prefix, libdir or
rhome (the PDF manuals are installed under the R home
directory). (make install-info needs Perl installed
if there is no command install-info on the system.)

More precise control is possible. For info, the setting used is that of
infodir (default prefix/info, set by configure
option --infodir). The PDF files are installed into the R
doc tree, set by the make variable rdocdir.

A staged installation is possible, that it is installing R into a
temporary directory in order to move the installed tree to its final
destination. In this case prefix (and so on) should reflect the
final destination, and DESTDIR should be used: see
https://www.gnu.org/prep/standards/html_node/DESTDIR.html.

You can optionally install the run-time tests that are part of
make check-all by

2.6 Sub-architectures

Some platforms can support closely related builds of R which can
share all but the executables and dynamic objects. Examples include
builds under Linux and Solaris for different CPUs or 32- and
64-bit builds.

R supports the idea of architecture-specific builds, specified by
adding ‘r_arch=name’ to the configure line. Here
name can be anything non-empty, and is used to name subdirectories
of lib, etc, include and the package libs
subdirectories. Example names from other software are the use of
sparcv9 on Sparc Solaris and 32 by gcc on
‘x86_64’ Linux.

If you have two or more such builds you can install them over each other
(and for 32/64-bit builds on one architecture, one build can be done
without ‘r_arch’). The space savings can be considerable: on
‘x86_64’ Linux a basic install (without debugging symbols) took
74Mb, and adding a 32-bit build added 6Mb. If you have installed
multiple builds you can select which build to run by

R --arch=name

and just running ‘R’ will run the last build that was installed.

R CMD INSTALL will detect if more than one build is installed and
try to install packages with the appropriate library objects for each.
This will not be done if the package has an executable configure
script or a src/Makefile file. In such cases you can install for
extra builds by

R --arch=name CMD INSTALL --libs-only pkg1pkg2 …

If you want to mix sub-architectures compiled on different platforms
(for example ‘x86_64’ Linux and ‘i686’ Linux), it is
wise to use explicit names for each, and you may also need to set
libdir to ensure that they install into the same place.

When sub-architectures are used the version of Rscript in
e.g. /usr/bin will be the last installed, but
architecture-specific versions will be available in e.g.
/usr/lib64/R/bin/exec${R_ARCH}. Normally all installed
architectures will run on the platform so the architecture of
Rscript itself does not matter. The executable
Rscript will run the R script, and at that time the
setting of the R_ARCH environment variable determines the
architecture which is run.

When running post-install tests with sub-architectures, use

R --arch=name CMD make check[-devel|all]

to select a sub-architecture to check.

Sub-architectures are also used on Windows, but by selecting executables
within the appropriate bin directory,
R_HOME/bin/i386 or R_HOME/bin/x64. For
backwards compatibility with R < 2.12.0, there are executables
R_HOME/bin/R.exe or R_HOME/bin/Rscript.exe:
these will run an executable from one of the subdirectories, which one
being taken first from the
R_ARCH environment variable, then from the
--arch command-line option8 and finally from the
installation default (which is 32-bit for a combined 32/64 bit R
installation).

2.6.1 Multilib

On Linux9, there is an alternative mechanism for mixing 32-bit and 64-bit
libraries known as multilib. If a Linux distribution supports
multilib, then parallel builds of R may be installed in the
sub-directories lib (32-bit) and lib64 (64-bit). The
build to be run may then be selected using the setarch
command. For example, a 32-bit build may be run by

setarch i686 R

The setarch command is only operational if both 32-bit and
64-bit builds are installed. If there is only one installation of R,
then this will always be run regardless of the architecture specified
by the setarch command.

There can be problems with installing packages on the non-native
architecture. It is a good idea to run e.g. setarch i686 R for
sessions in which packages are to be installed, even if that is the only
version of R installed (since this tells the package installation
code the architecture needed).

At present there is a potential problem with packages using Java, as
the post-install for a ‘i686’ RPM on ‘x86_64’ Linux
reconfigures Java and will find the ‘x86_64’ Java. If you know
where a 32-bit Java is installed you may be able to run (as root)

When this mechanism is used, the version of Rscript in
e.g. /usr/bin will be the last installed, but an
architecture-specific version will be available in
e.g. /usr/lib64/R/bin. Normally all installed architectures
will run on the platform so the architecture of Rscript does
not matter.

2.7 Other Options

There are many other installation options, most of which are listed by
configure --help. Almost all of those not listed elsewhere in
this manual are either standard autoconf options not relevant
to R or intended for specialist uses by the R developers.

One that may be useful when working on R itself is the option
--disable-byte-compiled-packages, which ensures that the base
and recommended packages are lazyloaded but not byte-compiled.
(Alternatively the (make or environment) variable
R_NO_BASE_COMPILE can be set to a non-empty value for the duration
of the build.)

Option --with-internal-tzcode makes use of R’s own code and
copy of the Olson database for managing timezones. This will be
preferred where there are issues with the system implementation, usually
involving times after 2037 or before 1916. An alternative time-zone
directory10 can be used, pointed
to by environment variable TZDIR: this should contain files such
as Europe/London. On all tested OSes the system timezone was
deduced correctly, but if necessary it can be set as the value of
environment variable TZ.

2.8 Testing an Installation

Full testing is possible only if the test files have been installed with

make install-tests

which populates a tests directory in the installation.

If this has been done, two testing routes are available.
The first is to move to the home directory of the R installation
(as given by R.home()) and run

cd tests
## followed by one of
../bin/R CMD make check
../bin/R CMD make check-devel
../bin/R CMD make check-all

and other useful targets are test-BasePackages and
test-Recommended to the run tests of the standard and
recommended packages (if installed) respectively.

This re-runs all the tests relevant to the installed R (including for
example code in the package vignettes), but not for example the ones
checking the example code in the manuals nor making the standalone Rmath
library. This can occasionally be useful when the operating environment
has been changed, for example by OS updates or by substituting the
BLAS (see Shared BLAS).

Parallel checking of packages may be possible: set the environment
variable TEST_MC_CORES to the maximum number of processes to be
run in parallel. This affects both checking the package examples (part
of make check) and package sources (part of make
check-devel and make check-recommended). It does require a
make command which supports the make -j n
option: most do but on Solaris you need to select GNU make or
dmake. Where parallel checking of package sources is done, a log
file pngname.log is left in the tests directory for
inspection.

Alternatively, the installed R can be run, preferably with
--vanilla. Then

runs the basic tests and then all the tests on the standard and
recommended packages. These tests can be run from anywhere: the basic
tests write their results in the tests folder of the R home
directory and run fewer tests than the first approach: in particular
they do not test things which need Internet access—that can be tested
by

testInstalledBasic("internet")

(On Windows that runs the tests using whichever of internal or WinInet
internet functions has been selected for that session: to test both run
this twice selecting both options using setInternet2.)

These tests work best if diff (in Rtools*.exe for
Windows users) is in the path.

It is possible to test the installed packages (but not their
package-specific tests) by testInstalledPackages even if
make install-tests was not run.

Note that the results may depend on the language set for times and
messages: for maximal similarity to reference results you may want to
try setting (before starting the R session)

3 Installing R under Windows

The bin/windows directory of a CRAN site contains
binaries for a base distribution and a large number of add-on packages
from CRAN to run on 32- or 64-bit Windows (XP or later) on
‘ix86’ and ‘x86_64’ CPUs.

Your file system must allow long file names (as is likely except
perhaps for some network-mounted systems).

Installation is via the installer
R-3.2.1patched-win.exe. Just double-click on the icon and
follow the instructions. When installing on a 64-bit version of Windows
the options will include 32- or 64-bit versions of R (and the default is
to install both). You can uninstall R from the Control Panel.

Note that you will be asked to choose a language for installation, and
that choice applies to both installation and un-installation but not to
running R itself.

3.1 Building from source

R can be built as either a 32-bit or 64-bit application on Windows:
to build the 64-bit application you need a 64-bit edition of Windows:
such an OS can also be used to build 32-bit R.

The standard installer combines 32-bit and 64-bit builds into a single
executable which can then be installed into the same location and share
all the files except the .exe and .dll files and some
configuration files in the etc directory.

Building is only tested in a 8-bit locale: using a multi-byte locale (as
used for CJK languages) is unsupported and may not work (the scripts do
try to select a ‘C’ locale; Windows may not honour this).

NB: The build process is currently being changed to require
external binary distributions of third-party software. Their location
is set using macro EXT_LIBS with default setting
$(LOCAL_SOFT); the $(LOCAL_SOFT) macro defaults to
$(R_HOME)/extsoft. This directory can be populated using
make rsync-extsoft. The location can be overridden by
setting EXT_LIBS to a different path in
src/gnuwin32/MkRules.local. A suitable collection of files can
also be obtained from
https://CRAN.R-project.org/bin/windows/extsoft or
https://www.stats.ox.ac.uk/pub/Rtools/libs.html.

The Rtools*.exe executable installer described in The Windows toolset also includes some source files in addition to the R
source as noted below. You should run it first, to obtain a working
tar and other necessities. Choose a “Full installation”, and
install the extra files into your intended R source directory, e.g.
C:/R. The directory name should not contain spaces. We
will call this directory R_HOME below.

3.1.2 Getting the source files

You need to collect the following sets of files:

Get the R source code tarball R-3.2.1.tar.gz from
CRAN. Open a command window (or another shell) at directory
R_HOME, and run

tar -xf R-3.2.1.tar.gz

to create the source tree in R_HOME. Beware: do use
tar to extract the sources rather than tools such as WinZip.
If you are using an account with administrative privileges you may get a
lot of messages which can be suppressed by

tar --no-same-owner -xf R-3.2.1.tar.gz

or perhaps better, set the environment variable TAR_OPTIONS to the
value ‘--no-same-owner --no-same-permissions’.

It is also possible to obtain the source code using Subversion; see
Obtaining R for details.

If you are not using a tarball you need to obtain copies of the
recommended packages from CRAN. Put the .tar.gz files
in R_HOME/src/library/Recommended and run make
link-recommended. If you have an Internet connection, you can do this
automatically by running in R_HOME/src/gnuwin32

make rsync-recommended

The binary distributions of external software. Download

https://www.stats.ox.ac.uk/pub/Rtools/goodies/multilib/local320.zip

create an empty directory, say c:/R/extsoft, and unpack it in
that directory by e.g.

unzip local320.zip -d c:/R/extsoft

Make a local copy of the configuration rules by

cd R_HOME/src/gnuwin32
cp MkRules.dist MkRules.local

and edit MkRules.local, uncommenting EXT_LIBS and setting
it to the appropriate path (in our example c:/R/extsoft).

Look through the file MkRules.local and make any other changes
needed: in particular, this is where a 64-bit build is selected and the
locations are set of external software for ICU collation and the
cairo-based devices.

The following additional item is normally installed by
Rtools31.exe. If instead you choose to do a completely manual
build you will also need

The Tcl/Tk support files are contained in Rtools31.exe and
available as .zip files from
https://www.stats.ox.ac.uk/pub/Rtools. Please make sure you
install the right version: there is a 32-bit version and a 64-bit
version. They should be installed to R_HOME, creating
directory Tcl there.

3.1.3 Building the core files

Set the environment variable TMPDIR to the absolute path to a
writable directory, with a path specified with forward slashes and no
spaces. (The default is /tmp, which may not be useful on
Windows.)

You may need to compile under a case-honouring file system: we found
that a samba-mounted file system (which maps all file names to
lower case) did not work.

Open a command window at R_HOME/src/gnuwin32, then run

make all recommended vignettes

and sit back and wait while the basic compile takes place.

Notes:

We have had reports that earlier versions of anti-virus software locking
up the machine, but not for several years. However, aggressive
anti-virus checking such as the on-access scanning of Sophos can slow
the build down several-fold.

You can run a parallel make by e.g.

make -j4 all
make -j4 recommended
make vignettes

but this is only likely to be worthwhile on a multi-core machine with
ample memory, and is not 100% reliable.

It is possible (mainly for those working on R itself) to set the
(make or environment) variable R_NO_BASE_COMPILE to a non-empty
value, which inhibits the byte-compilation of the base and recommended
packages.

3.1.4 Building the cairo devices

The devices based on cairographics (svg, cairo_pdf,
cairo_ps and the type = "cairo" versions of png,
jpeg, tiff and bmp) are implemented in a separate
DLL winCairo.dll which is loaded when one of these devices is
first used. It is not built by default, and needs to be built (after
make all) by make cairodevices.

To enable the building of these devices you need to install the static
cairographics libraries built by Simon Urbanek at
https://www.rforge.net/Cairo/files/cairo-current-win.tar.gz. Set
the macro ‘CAIRO_HOME’ in MkRules.local. (Note that this
tarball unpacks with a top-level directory src/:
‘CAIRO_HOME’ needs to include that directory in its path.)

If a test fails, there will almost always be a .Rout.fail file in
the directory being checked (often tests/Examples or
tests): examine the file to help pinpoint the problem.

Parallel checking of package sources (part of make check-devel
and make check-recommended) is possible: see the environment
variable TEST_MC_CORES to the maximum number of processes to be
run in parallel.

3.1.8 Building the manuals

If you want to make the info versions (not including the Reference
Manual), use

cd ../../doc/manual
make -f Makefile.win info

(all assuming you have pdftex/pdflatex installed and
in your path).

See the Making the manuals section in the Unix-alike section for setting
options such as the paper size and the fonts used.

By default it is assumed that texinfo is not installed, and the
manuals will not be built. The comments in file MkRules.dist
describe settings to build them. (Copy that file to
MkRules.local and edit it.) The texinfo 5.x package for
use on Windows is available at
https://www.stats.ox.ac.uk/pub/Rtools/: you will also need to
install Perl11

3.1.9 Building the Inno Setup installer

You need to have the files for a complete R build, including bitmap and
Tcl/Tk support and the manuals (which requires texinfo installed),
as well as the recommended packages and Inno Setup (see The Inno Setup installer).

Once everything is set up

make distribution
make check-all

will make all the pieces and the installer and put them in the
gnuwin32/cran subdirectory, then check the build. This works by
building all the parts in the sequence:

rbuild (the executables, the FAQ docs etc.)
rpackages (the base packages)
htmldocs (the HTML documentation)
cairodevices (the cairo-based graphics devices)
recommended (the recommended packages)
vignettes (the vignettes in base packages: only needed if building from an svn checkout)
manuals (the PDF manuals)
rinstaller (the install program)
crandir (the CRAN distribution directory, only for 64-bit builds)

The parts can be made individually if a full build is not needed, but
earlier parts must be built before later ones. (The Makefile
doesn’t enforce this dependency—some build targets force a lot of
computation even if all files are up to date.) The first four targets
are the default build if just make (or make all) is
run.

Parallel make is not supported and likely to fail.

If you want to customize the installation by adding extra packages,
replace make rinstaller by something like

make rinstaller EXTRA_PKGS='pkg1 pkg2 pkg3'

An alternative way to customize the installer starting with a binary
distribution is to first make an installation of R from the standard
installer, then add packages and make other customizations to that
installation. Then (after having customized file MkRules,
possibly viaMkRules.local, and having made R in the
source tree) in src/gnuwin32/installer run

make myR IMAGEDIR=rootdir

where rootdir is the path to the root of the customized
installation (in double quotes if it contains spaces or backslashes).

Both methods create an executable with a standard name such as
R-3.2.1patched-win.exe, so please rename it to indicate that
it is customized. If you intend to distribute a customized
installer please do check that license requirements are met – note that
the installer will state that the contents are distributed under GPL
and this has a requirement for you to supply the complete sources
(including the R sources even if you started with a binary distribution
of R, and also the sources of any extra packages (including their
external software) which are included).

The defaults for the startup parameters may also be customized. For example

make myR IMAGEDIR=rootdir MDISDI=1

will create an installer that defaults to installing R to run in SDI
mode. See src/gnuwin32/installer/Makefile for the names and
values that can be set.

The standard CRAN distribution of a 32/64-bit installer is
made by first building 32-bit R (just

make 32-bit

is needed), and then (in a separate directory) building 64-bit R with
the macro HOME32 set in file MkRules.local to the
top-level directory of the 32-bit build. Then the make
rinstaller step copies the files that differ between architectures from
the 32-bit build as it builds the installer image.

3.1.10 Building the MSI installer

It is also possible to build an installer for use with Microsoft
Installer. This is intended for use by sysadmins doing automated
installs, and is not recommended for casual use.

It makes use of the Windows Installer XML (WiX) toolkit version
3.5 (or perhaps later, untested) available from
http://wixtoolset.org/. Once WiX is installed, set the path to
its home directory in MkRules.local.

You need to have the files for a complete R build, including bitmap and
Tcl/Tk support and the manuals, as well as the recommended packages.
There is no option in the installer to customize startup options, so
edit etc/Rconsole and etc/Rprofile.site to set these as
required. Then

cd installer
make msi

which will result in a file with a name like
R-3.2.1patched-win32.msi. This can be double-clicked to be
installed, but those who need it will know what to do with it (usually
by running msiexec /i with additional options). Properties
that users might want to set from the msiexec command line
include ‘ALLUSERS’, ‘INSTALLDIR’ (something like
c:\Program Files\R\R-3.2.1patched) and ‘RMENU’ (the path
to the ‘R’ folder on the start menu) and ‘STARTDIR’ (the
starting directory for R shortcuts, defaulting to something like
c:\Users\name\Documents\R).

The MSI installer can be built both from a 32-bit build of R
(R-3.2.1patched-win32.msi) and from a 64-bit build of R
(R-3.2.1patched-win64.msi, optionally including 32-bit files
by setting the macro HOME32, when the name is
R-3.2.1patched-win.msi). Unlike the main installer, a 64-bit
MSI installer can only be run on 64-bit Windows.

Thanks to David del Campo (Dept of Statistics, University of Oxford)
for suggesting WiX and building a prototype installer.

3.1.11 64-bit Windows builds

To build a 64-bit version of R you need a 64-bit toolchain: the only one
discussed here is based on the work of the MinGW-w64 project
(http://sourceforge.net/projects/mingw-w64/, but commercial
compilers such as those from Intel and PGI could be used (and have been
by R redistributors).

Support for MinGW-w64 was developed in the R sources over the period
2008–10 and was first released as part of R 2.11.0. The assistance
of Yu Gong at a crucial step in porting R to MinGW-w64 is gratefully
acknowledged, as well as help from Kai Tietz, the lead developer of the
MinGW-w64 project.

Windows 64-bit is now completely integrated into the R and package
build systems: a 64-bit build is selected in file MkRules.local.

runs the basic tests and then all the tests on the standard and
recommended packages. These tests can be run from anywhere: they write
some of their results in the tests folder of the R home
directory (as given by R.home()), and hence may need to be run
under the account used to install R.

The results of example(md5sums) when testing tools will
differ from the reference output as some files are installed with
Windows’ CRLF line endings.

4 Installing R under OS X

The front page of a CRAN site has a link ‘Download R for OS
X’. Click on that, then download the file R-3.2.1.pkg
and install it. This runs on OS X 10.9 and later (Mavericks, Yosemite,
El Capitan, …).

There may be12 a
separate installer package R-3.2.1-snowleopard.pkg,
which runs on OS X 10.6 and later (Snow Leopard, Lion, Mountain Lion,
Mavericks, Yosemite, …); it is a 64-bit (‘x86_64’) build
which should run on all Macs from mid-2008 on.

Installers for R-patched and R-devel are usually available from
http://r.research.att.com, including a
R-3-2-branch-snowleopard-signed.pkg version for R-patched.

For some older versions of the OS you can in principle (it is little
tested) install R from the sources.

It is important that if you use a binary installer package that your OS
is fully updated: look at ‘Updates’ from the ‘App Store’ to be sure.
(If using XQuartz, check that is current.)

To install, just double-click on the icon of the file you downloaded.
At the ‘Installation Type’ stage, note the option to ‘Customize’. This
currently shows three components. Everyone will need the ‘R Framework’
component: the ‘R GUI’ and ‘Tcl/Tk’ components are optional (the latter
being needed to use package tcltk, and requires an X sub-system to
be installed: see OS X.)

This is an Apple Installer package. If you encounter any problem during
the installation, please check the Installer log by clicking on the
“Window” menu and item “Installer Log”. The full output (select
“Show All Log”) is useful for tracking down problems.

If you update your OS X version, you should re-install R: the
installer tailors the installation to the current version of the OS.

4.1 Running R under OS X

There are two ways to run R on OS X from a CRAN binary
distribution.

There is a GUI console normally installed with the R icon in
/Applications which you can run by double-clicking (e.g. from
Launchpad or Finder). This is usually referred to as R.APP to
distinguish it from command-line R: its user manual is currently part
of the OS X FAQ at
https://cran.r-project.org/bin/macosx/RMacOSX-FAQ.html and
can be viewed from R.APP’s ‘Help’ menu.

You can run command-line R from a Terminal like any other Unix-alike:
see the next chapter of this manual. There are some small differences
which may surprise users of R on other platforms, notably the default
location of the personal library directory (under ~/Library/R,
e.g. ~/Library/R/3.1/library), and that warnings, messages and
other output to stderr are highlighted in bold.

It has been reported that running R.APP under Yosemite may fail if no
preferences are stored, so if it fails when launched for the very first
time, try it again (the first attempt will store some preferences).

Ensure that the console is completely visible (or at least the activity
indicator at the top right corner is visible).

Call ‘Get Info’ on the application (e.g. from Finder). This may
have two tick boxes in the ‘General’ panel: click the one named ‘Prevent
App Nap’ if it is not already ticked. (This only available for builds
made prior to Mavericks.)

Using the X11 device or the X11-based versions of View()
and edit() for data frames and matrices (the latter are the
default for command-line R but not R.APP) requires an X sub-system
to be installed: see OS X. (As do the tcltk package and
some third-party packages.)

4.2 Uninstalling under OS X

R for OS X consists of two parts: the GUI (R.APP) and the R
framework. The un-installation is as simple as removing those folders
(e.g. by dragging them into the Trash). The typical installation will
install the GUI into the /Applications/R.app folder and the R
framework into the /Library/Frameworks/R.framework folder. This
does leave some links in /usr/bin.

If you want to get rid of R more completely using a Terminal, simply
run (prepend sudo if needed):

The installation consisted of three Apple packages:
org.r-project.R.x86_64.fw.pkg,
org.r-project.R.x86_64.GUI.pkg and
org.r-project.x86_64.tcltk.x11 (not all of which need be
installed). You can use pkgutil --forget if you want the Apple
Installer to forget about the package without deleting its files (useful
for the R framework when installing multiple R versions in parallel),
or after you have deleted the files.

Uninstalling the Tcl/Tk component (which is installed under
/usr/local) is not simple. You can list the files it installed
in a Terminal by

4.3 Multiple versions

The installer will remove any previous version of the R framework
which it finds installed. This can be avoided by using pkgutil
--forget (see the previous section). However, note that different
versions are installed under
/Library/Frameworks/R.framework/Versions as 3.0,
3.1 and so on, so it is not possible to have different
‘3.x.y’ versions installed for the same ‘x’.

A version of R can be run directly from the command-line as e.g.

/Library/Frameworks/R.framework/Versions/3.1/Resources/bin/R

However, R.APP will always run the ‘current’ version, that is the last
installed version. A small utility, Rswitch.app (available at
http://r.research.att.com/#other), can be used to change the
‘current’ version. This is of limited use as R.APP is compiled
against a particular version of R and will likely crash if switched
to an earlier version. This may allow you to install a development
version of R (de-selecting R.APP) and then switch back to the
release version.

5 Running R

How to start R and what command-line options are available is discussed
in Invoking R in An Introduction to R.

You should ensure that the shell has set adequate resource limits: R
expects a stack size of at least 8MB and to be able to open at least 256
file descriptors. (Any modern OS should have default limits at least as
large as these, but apparently NetBSD may not. Use the shell command
ulimit (sh/bash) or limit
(csh/tcsh) to check.)

R makes use of a number of environment variables, the default values
of many of which are set in file R_HOME/etc/Renviron (there
are none set by default on Windows and hence no such file). These are
set at configure time, and you would not normally want to
change them – a possible exception is R_PAPERSIZE (see Setting paper size). The paper size will be deduced from the ‘LC_PAPER’
locale category if it exists and R_PAPERSIZE is unset, and this
will normally produce the right choice from ‘a4’ and ‘letter’
on modern Unix-alikes (but can always be overridden by setting
R_PAPERSIZE).

Various environment variables can be set to determine where R creates
its per-session temporary directory. The environment variables
TMPDIR, TMP and TEMP are searched in turn and the
first one which is set and points to a writable area is used. If none
do, the final default is /tmp on Unix-alikes and the value of
R_USER on Windows. The path should be an absolute path not
containing spaces (and it is best to avoid non-alphanumeric characters
such as +).

Some Unix-alike systems are set up to remove files and directories
periodically from /tmp, for example by a cron job
running tmpwatch. Set TMPDIR to another directory
before starting long-running jobs on such a system.

Note that TMPDIR will be used to execute configure
scripts when installing packages, so if /tmp has been mounted as
‘noexec’, TMPDIR needs to be set to a directory from which
execution is allowed.

6 Add-on packages

It is helpful to use the correct terminology. A package is
loaded from a library by the function library(). Thus a
library is a directory containing installed packages; the main library
is R_HOME/library, but others can be used, for example by
setting the environment variable R_LIBS or using the R function
.libPaths().

6.1 Default packages

(plus, of course, base) and this can be changed by setting the
option in startup code (e.g. in ~/.Rprofile). It is initially
set to the value of the environment variable R_DEFAULT_PACKAGES if
set (as a comma-separated list). Setting R_DEFAULT_PACKAGES=NULL
ensures that only package base is loaded.

Changing the set of default packages is normally used to reduce the set
for speed when scripting: in particular not using methods will
reduce the start-up time by a factor of up to two (and this is done by
Rscript). But it can also be used to customize R, e.g.
for class use.

6.2 Managing libraries

R packages are installed into libraries, which are
directories in the file system containing a subdirectory for each
package installed there.

R comes with a single library, R_HOME/library which is
the value of the R object ‘.Library’ containing the standard and
recommended13 packages.
Both sites and users can create others and make use of them (or not) in
an R session. At the lowest level ‘.libPaths()’ can be used to
add paths to the collection of libraries or to report the current
collection.

R will automatically make use of a site-specific library
R_HOME/site-library if this exists (it does not in a
vanilla R installation). This location can be overridden by
setting14 ‘.Library.site’ in
R_HOME/etc/Rprofile.site, or (not recommended) by setting
the
environment variable R_LIBS_SITE. Like ‘.Library’, the
site libraries are always included by ‘.libPaths()’.

Users can have one or more libraries, normally specified by the
environment variable R_LIBS_USER. This has a default value (to
see it, use ‘Sys.getenv("R_LIBS_USER")’ within an R session),
but that is only used if the corresponding directory actually exists
(which by default it will not).

Both R_LIBS_USER and R_LIBS_SITE can specify multiple
library paths, separated by colons (semicolons on Windows).

6.3 Installing packages

Packages may be distributed in source form or compiled binary form.
Installing source packages which contain C/C++/Fortran code requires
that compilers and related tools be installed. Binary packages are
platform-specific and generally need no special tools to install, but
see the documentation for your platform for details.

Note that you may need to specify implicitly or explicitly the library to
which the package is to be installed. This is only an issue if you have
more than one library, of course.

Ensure that the environment variable TMPDIR is either unset (and
/tmp exists and can be written in and executed from) or is the
absolute path to a valid temporary directory, not containing spaces.

For most users it suffices to call
‘install.packages(pkgname)’ or its GUI equivalent if the
intention is to install a CRAN package and internet access is
available.15 On most systems ‘install.packages()’
will allow packages to be selected from a list box (typically with
several thousand items).

To install packages from source on a Unix-alike use in a terminal

R CMD INSTALL -l /path/to/library pkg1pkg2 …

The part ‘-l /path/to/library’ can be omitted, in which case the
first library of a normal R session is used (that shown by
.libPaths()[1]).

There are a number of options available: use R CMD INSTALL --help
to see the current list.

Alternatively, packages can be downloaded and installed from within
R. First choose your nearest CRAN mirror using
chooseCRANmirror(). Then download and install packages
pkg1 and pkg2 by

> install.packages(c("pkg1", "pkg2"))

The essential dependencies of the specified packages will also be fetched.
Unless the library is specified (argument lib) the first library
in the library search path is used: if this is not writable, R will
ask the user (in an interactive session) if the default personal library
should be created, and if allowed to will install the packages there.

If you want to fetch a package and all those it depends on (in any way)
that are not already installed, use e.g.

> install.packages("Rcmdr", dependencies = TRUE)

install.packages can install a source package from a local
.tar.gz file (or a URL to such a file) by setting argument
repos to NULL: this will be selected automatically if the
name given is a single .tar.gz file.

install.packages can look in several repositories, specified as a
character vector by the argument repos: these can include a
CRAN mirror, Bioconductor, Omegahat, R-forge, rforge.net,
local archives, local files, …). Function
setRepositories() can select amongst those repositories that the
R installation is aware of.

Naive users sometimes forget that as well as installing a package, they
have to use library to make its functionality available.

6.3.1 Windows

What install.packages does by default is different on Unix-alikes
(except OS X) and Windows. On Unix-alikes it consults the list of
available source packages on CRAN (or other
repository/ies), downloads the latest version of the package sources,
and installs them (via R CMD INSTALL). On Windows it looks (by
default) first at the list of binary versions of packages
available for your version of R and downloads the latest versions (if
any). If no binary version is available or the source version is newer,
it will install the source versions of packages without compiled
C/C++/Fortran code, and offer to do so for those with, if make
is available (and this can be tuned by option
"install.packages.compile.from.source").

On Windows install.packages can also install a binary package
from a local zip file (or the URL of such a file) by setting
argument repos to NULL. Rgui.exe has a menu
Packages with a GUI interface to install.packages,
update.packages and library.

Windows binary packages for R are distributed as a single binary
containing either or both architectures (32- and 64-bit).

R CMD INSTALL works in Windows to install source packages. No
additional tools are needed if the package does not contain compiled
code, and install.packages(type="source") will work for such
packages (and for those with compiled code if the tools (see The Windows toolset) are in the path). We have seen occasional permission
problems after unpacking source packages on some systems: these have
been circumvented by setting the environment variable
R_INSTALL_TAR to ‘tar.exe’.

If you have only a source package that is known to work with current
R and just want a binary Windows build of it, you could make use of
the building service offered at
http://win-builder.r-project.org/.

For almost all packages R CMD INSTALL will attempt to install
both 32- and 64-bit builds of a package if run from a 32/64-bit install
of R. It will report success if the installation of the architecture
of the running R succeeded, whether or not the other
architecture was successfully installed. The exceptions are packages
with a non-empty configure.win script or which make use of
src/Makefile.win. If configure.win does something
appropriate to both architectures use16 option
--force-biarch: otherwise R CMD INSTALL
--merge-multiarch can be applied to a source tarball to merge separate
32- and 64-bit installs. (This can only be applied to a tarball, and
will only succeed if both installs succeed.)

If you have a package without compiled code and no Windows-specific
help, you can zip up an installation on another OS and install from that
zip file on Windows. However, such a package can be installed from the
sources on Windows without any additional tools.

There is provision to make use of a system-wide library of installed
external software by setting the make variable
LOCAL_SOFT, to give an equivalent of /usr/local on a
Unix-alike. This can be set in src/gnuwin/MkRules.local when
R is built from sources (see the comments in
src/gnuwin/MkRules.dist), or in file17etc/i386/Makeconf or etc/x64/Makeconf for an
installed version of R. The version used by CRAN can be
installed as described in Building from source.

6.3.2 OS X

On OS X install.packages works as it does on other Unix-alike
systems, but there are additional types starting with mac.binary
(available for the CRAN distribution but not when compiling
from source: mac.binary.mavericks for a ‘Mavericks’ build with
"default" a synonym for the appropriate variant) which can be
passed to install.packages in order to download and install
binary packages from a suitable repository. These OS X binary package
files have the extension ‘.tgz’. The R.APP GUI provides menus
for installation of either binary or source packages, from
CRAN or local files.

On R builds using binary packages, the default is type both:
this looks first at the list of binary packages available for your
version of R and installs the latest versions (if any). If no binary
version is available or the source version is newer, it will install the
source versions of packages without compiled C/C++/Fortran code and offer
to do so for those with, if make is available.

Note that most binary packages including compiled code are tied to a
particular series (e.g. R 3.2.x or 3.1.x) of R.

You should not attempt to mix-and-match binary packages built for the
‘Snow Leopard’ and ‘Mavericks’ CRAN distributions: doing so is
likely to lead to crashes or failures to load.

Installing source packages which do not contain compiled code should
work with no additional tools. For others you will need the
‘Command Line Tools’ for Xcode and compilers which match those
used to build R: see OS X.

Package rJava and those which depend on it need a Java runtime
installed and several packages need X11 installed, including those using
Tk. For Mountain Lion and later see OS X and Java (OS X).

Tcl/Tk extensions BWidget and Tktable are part of the
Tcl/Tk contained in the R installer. These are required by a number
of CRAN and Bioconductor packages.

The default compilers specified in
/Library/Frameworks/R.framework/Resources/etc/Makeconf depend on
the version of OS X under which R was installed, and are appropriate
to the latest version of the command-line tools for that version
of OS X. The settings can be changed, either by editing that file or in
a file such as ~/.R/Makevars (see the next section). Entries
which may need to be changed include ‘CC’, ‘CXX’, ‘FC’,
‘F77’, ‘FLIBS’ and the corresponding flags, and perhaps
‘CXXCPP’, ‘DYLIB_LD’, ‘MAIN_LD’, ‘SHLIB_CXXLD’,
‘SHLIB_FCLD’ and ‘SHLIB_LD’.

So for example you could select clang for both C and C++ with
extensive checking by having in ~/.R/Makevars

6.3.3 Customizing package compilation

The R system and package-specific compilation flags can be overridden or
added to by setting the appropriate Make variables in the personal file
HOME/.R/Makevars-R_PLATFORM (but
HOME/.R/Makevars.win or HOME/.R/Makevars.win64
on Windows), or if that does not exist, HOME/.R/Makevars,
where ‘R_PLATFORM’ is the platform for which R was built, as
available in the platform component of the R variable
R.version. An alternative personal file can be specified
via the environment variable R_MAKEVARS_USER.

Package developers are encouraged to use this mechanism to enable a
reasonable amount of diagnostic messaging (“warnings”) when compiling,
such as e.g. -Wall -pedantic for tools from GCC, the Gnu
Compiler Collection.

Note that this mechanism can also be used when it necessary to change
the optimization level for a particular package. For example

There is also provision for a site-wide Makevars.site file under
R_HOME/etc (in a sub-architecture-specific directory if
appropriate). This is read immediately after Makeconf, and an
alternative file can be specified by environment variable
R_MAKEVARS_SITE.

6.3.4 Multiple sub-architectures

When installing packages from their sources, there are some extra
considerations on installations which use sub-architectures. These are
commonly used on Windows but can in principle be used on other
platforms.

When a source package is installed by a build of R which supports
multiple sub-architectures, the normal installation process installs the
packages for all sub-architectures. The exceptions are

Unix-alikes

where there is an configure script, or a file src/Makefile.

Windows

where there is a non-empty configure.win script, or a file
src/Makefile.win (with some exceptions where the package is known
to have an architecture-independent configure.win, or if
--force-biarch or field ‘Biarch’ in the DESCRIPTION
file is used to assert so).

In those cases only the current architecture is installed. Further
sub-architectures can be installed by

R CMD INSTALL --libs-only pkg

using the path to R or R --arch to select the
additional sub-architecture. There is also R CMD INSTALL
--merge-multiarch to build and merge the two architectures, starting
with a source tarball.

6.3.5 Byte-compilation

The base and recommended packages are byte-compiled by default. Other
packages can be byte-compiled on installation by using R CMD
INSTALL with option --byte-compile or by
install.packages(type = "source", INSTALL_opts =
"--byte-compile").

Not all contributed packages work correctly when byte-compiled (for
example because they interfere with the sealing of namespaces). For
most packages (especially those which make extensive use of compiled
code) the speed-up is small. Unless a package is used frequently the
time spent in byte-compilation can outweigh the time saved in execution:
also byte-compilation can add substantially to the installed size of the
package.

Byte-compilation can be controlled on a per-package basis by the
‘ByteCompile’ field in the DESCRIPTION file.

6.4 Updating packages

The command update.packages() is the simplest way to ensure that
all the packages on your system are up to date. It downloads the list
of available packages and their current versions, compares it with those
installed and offers to fetch and install any that have later versions
on the repositories.

An alternative interface to keeping packages up-to-date is provided by
the command packageStatus(), which returns an object with
information on all installed packages and packages available at multiple
repositories. The print and summary methods give an
overview of installed and available packages, the upgrade method
offers to fetch and install the latest versions of outdated packages.

One sometimes-useful additional piece of information that
packageStatus() returns is the status of a package, as
"ok", "upgrade" or "unavailable" (in the currently
selected repositories). For example

6.6 Setting up a package repository

Utilities such as install.packages can be pointed at any
CRAN-style repository, and R users may want to set up their
own. The ‘base’ of a repository is a URL such as
http://www.omegahat.org/R/: this must be an URL scheme that
download.packages supports (which also includes ‘ftp://’ and
‘file://’ and on most systems ‘https://’). Under that base
URL there should be directory trees for one or more of the following
types of package distributions:

"source": located at src/contrib and containing
.tar.gz files. Other forms of compression can be used, e.g.
.tar.bz2 or .tar.xz files. Complete repositories contain
the sources corresponding to any binary packages, and in any case it is
wise to have a src/contrib area with a possibly empty
PACKAGES file.

"win.binary": located at bin/windows/contrib/x.y for
R versions x.y.z and containing .zip files for Windows.

"mac.binary.mavericks": located at
bin/macosx/mavericks/contrib/3.y for the CRAN build for
‘Mavericks’ (and later) for R versions 3.y.z, containing
.tgz files.

"mac.binary.leopard": located at
bin/macosx/leopard/contrib/2.y for R versions
2.y.z and containing .tgz files.

(Areas "mac.binary.leopard" and "mac.binary" are no longer
in use.)

Each terminal directory must also contain a PACKAGES file. This
can be a concatenation of the DESCRIPTION files of the packages
separated by blank lines, but only a few of the fields are needed. The
simplest way to set up such a file is to use function
write_PACKAGES in the tools package, and its help explains
which fields are needed. Optionally there can also be a
PACKAGES.gz file, a gzip-compressed version of
PACKAGES—as this will be downloaded in preference to
PACKAGES it should be included for large repositories. (If you
have a mis-configured server that does not report correctly non-existent
files you may need PACKAGES.gz.)

To add your repository to the list offered by setRepositories(),
see the help file for that function.

Incomplete repositories are better specified via a
contriburl argument than via being set as a repository.

A repository can contain subdirectories, when the descriptions in the
PACKAGES file of packages in subdirectories must include a line
of the form

6.7 Checking installed source packages

It can be convenient to run R CMD check on an installed
package, particularly on a platform which uses sub-architectures. The
outline of how to do this is, with the source package in directory
pkg (or a tarball filename):

where --extra-arch selects only those checks which depend on
the installed code and not those which analyse the sources. (If
multiple sub-architectures fail only because they need different
settings, e.g. environment variables, --no-multiarch may need
to be added to the INSTALL lines.) On Unix-alikes the
architecture to run is selected by --arch: this can also be
used on Windows with R_HOME/bin/R.exe, but it is more usual
to select the path to the Rcmd.exe of the desired
architecture.

So on Windows to install, check and package for distribution a source
package from a tarball which has been tested on another platform one
might use

7 Internationalization and Localization

Internationalization refers to the process of enabling support
for many human languages, and localization to adapting to a
specific country and language.

Current builds of R support all the character sets that the
underlying OS can handle. These are interpreted according to the
current locale, a sufficiently complicated topic to merit a
separate section. Note though that R has no built-in support for
right-to-left languages and bidirectional output, relying on the OS
services. For example, how character vectors in UTF-8 containing both
English digits and Hebrew characters are printed is OS-dependent (and
perhaps locale-dependent).

The other aspect of the internationalization is support for the
translation of messages. This is enabled in almost all builds of R.

7.1 Locales

A locale is a description of the local environment of the user,
including the preferred language, the encoding of characters, the
currency used and its conventions, and so on. Aspects of the locale are
accessed by the R functions Sys.getlocale and
Sys.localeconv.

The system of naming locales is OS-specific. There is quite wide
agreement on schemes, but not on the details of their implementation. A
locale needs to specify

A ‘territory’, used mainly to specify the currency. These are generally
specified by an upper-case two-character abbreviation following ISO 3166
(see e.g. https://en.wikipedia.org/wiki/ISO_3166).

A charset encoding, which determines both how a byte stream should be
divided into characters, and which characters the subsequences of bytes
represent. Sometimes the combination of language and territory is used
to specify the encoding, for example to distinguish between traditional
and simplified Chinese.

Optionally, a modifier, for example to indicate that Austria is to be
considered pre- or post-Euro. The modifier is also used to indicate the
script (@latin, @cyrillic for Serbian, @iqtelif)
or language dialect (e.g. @saaho, a dialect of Afar, and
@bokmal and @nynorsk, dialects of Norwegian regarded by
some OSes as separate languages, no and nn).

R is principally concerned with the first (for translations) and
third. Note that the charset may be deducible from the language, as
some OSes offer only one charset per language.

7.1.1 Locales under Unix-alikes

Modern Linux uses the XPG18 locale specifications which have the form
‘en_GB’, ‘en_GB.UTF-8’, ‘aa_ER.UTF-8@saaho’,
‘de_AT.iso885915@euro’, the components being in the order listed
above. (See man locale and locale -a for more
details.) Similar schemes are used by most Unix-alikes: some (including
some distributions of Linux) use ‘.utf8’ rather than ‘.UTF-8’.

Note that whereas UTF-8 locales are nowadays almost universally used,
locales such as ‘en_GB’ use 8-bit encodings for backwards
compatibility.

7.1.2 Locales under Windows

Windows also uses locales, but specified in a rather less concise way.
Most users will encounter locales only via drop-down menus, but more
information and lists can be found at
https://msdn.microsoft.com/en-us/library/hzz3tw78(v=vs.80)
(or if Microsoft moves it yet again, search for ‘Windows language
country strings’).

It offers only one encoding per language.

Some care is needed with Windows’ locale names. For example,
chinese is Traditional Chinese and not Simplified Chinese as used
in most of the Chinese-speaking world.

7.1.3 Locales under OS X

OS X supports locales in its own particular way, but the R GUI tries to
make this easier for users. See
https://developer.apple.com/documentation/MacOSX/Conceptual/BPInternational/
for how users can set their locales. As with Windows, end users will
generally only see lists of languages/territories. Users of R in a
terminal may need to set the locale to something like ‘en_GB.UTF-8’
if it defaults to ‘C’ (as it sometimes does when logging in
remotely and for batch jobs: note whether Terminal sets the
LANG environment variable is an (advanced) preference, but does so
by default).

Internally OS X uses a form similar to Linux: the main difference from
other Unix-alikes is that where a character set is not specified it is
assumed to be UTF-8.

7.2 Localization of messages

The preferred language for messages is by default taken from the locale.
This can be overridden first by the setting of the environment variable
LANGUAGE and then19
by the environment variables LC_ALL, LC_MESSAGES and
LANG. (The last three are normally used to set the locale and so
should not be needed, but the first is only used to select the language
for messages.) The code tries hard to map locales to languages, but on
some systems (notably Windows) the locale names needed for the
environment variable LC_ALL do not all correspond to XPG language
names and so LANGUAGE may need to be set. (One example is
‘LC_ALL=es’ on Windows which sets the locale to Estonian and the
language to Spanish.)

It is usually possible to change the language once R is running
via (not Windows) Sys.setlocale("LC_MESSAGES",
"new_locale"), or by setting an environment variable such as
LANGUAGE, provided20 the language you are changing to can be output in
the current character set. But this is OS-specific, and has been known
to stop working on an OS upgrade.

Messages are divided into domains, and translations may be
available for some or all messages in a domain. R makes use of the
following domains.

Domain R for the C-level error and warning messages from the R
interpreter.

Domain R-pkg for the R stop, warning and
message messages in each package, including R-base for the
base package.

Domain pkg for the C-level messages in each package.

Domain RGui for the menus etc of the R for Windows GUI front-end.

Dividing up the messages in this way allows R to be extensible: as
packages are loaded, their message translation catalogues can be loaded
too.

R can be built without support for translations, but it is enabled by
default.

R-level and C-level domains are subtly different, for example in the way
strings are canonicalized before being passed for translation.

Translations are looked for by domain according to the currently
specified language, as specifically as possible, so for example an
Austrian (‘de_AT’) translation catalogue will be used in preference
to a generic German one (‘de’) for an Austrian user. However, if a
specific translation catalogue exists but does not contain a
translation, the less specific catalogues are consulted. For example,
R has catalogues for ‘en_GB’ that translate the Americanisms
(e.g., ‘gray’) in the standard messages into English.21 Two other examples: there are catalogues
for ‘es’, which is Spanish as written in Spain and these will by
default also be used in Spanish-speaking Latin American countries, and
also for ‘pt_BR’, which are used for Brazilian locales but not for
locales specifying Portugal.

Translations in the right language but the wrong charset are made use of
by on-the-fly re-encoding. The LANGUAGE variable (only) can be a
colon-separated list, for example ‘se:de’, giving a set of
languages in decreasing order of preference. One special value is
‘en@quot’, which can be used in a UTF-8 locale to have American
error messages with pairs of single quotes translated to Unicode directional
quotes.

If no suitable translation catalogue is found or a particular message is
not translated in any suitable catalogue, ‘English’22 is used.

8 Choosing between 32- and 64-bit builds

Almost all current CPUs have both 32- and 64-bit sets of
instructions. Most OSes running on such CPUs offer the choice
of building a 32-bit or a 64-bit version of R (and details are given
below under specific OSes). For most a 32-bit version is the default,
but for some (e.g., ‘x86_64’ Linux and OS X >= 10.6)
64-bit is.

All current versions of R use 32-bit integers and
ISO/IEC 6055923 double-precision reals, and so compute to
the same precision24 and with the same limits on the sizes of
numerical quantities. The principal difference is in the size of the
pointers.

64-bit builds have both advantages and disadvantages:

The total virtual memory space made available to a 32-bit process is
limited by the pointer size to 4GB, and on most OSes to 3GB (or even
2GB). The limits for 64-bit processes are much larger (e.g.
8–128TB).

R allocates memory for large objects as needed, and removes any
unused ones at garbage collection. When the sizes of objects become an
appreciable fraction of the address limit, fragmentation of the address
space becomes an issue and there may be no hole available that is the
size requested. This can cause more frequent garbage collection or the
inability to allocate large objects. As a guide, this will become an
issue with objects more than 10% of the size of the address space
(around 300Mb) or when the total size of objects in use is around one
third (around 1Gb).

Only 64-bit builds support ‘long vectors’, those with 2^{31} or
more elements (each of which needs 16GB of storage for a numeric
vector).

Most 32-bit OSes by default limit file sizes to 2GB (and this may also
apply to 32-bit builds on 64-bit OSes). This can often be worked
around: and configure selects suitable defines if this is
possible. (We have also largely worked around that limit on 32-bit
Windows.) 64-bit builds have much larger limits.

Because the pointers are larger, R’s basic structures are larger.
This means that R objects take more space and (usually) more time to
manipulate. So 64-bit builds of R will, all other things being
equal, run slower than 32-bit builds. (On Sparc Solaris the difference
was 15-20%.)

However, ‘other things’ may not be equal. In the specific case of
‘x86_64’ vs ‘ix86’, the 64-bit CPU has features
(such as SSE2 instructions) which are guaranteed to be present but are
optional on the 32-bit CPU, and also has more general-purpose registers.
This means that on chips like a desktop Intel Core 2 Duo the vanilla
64-bit version of R has been around 10% faster on both Linux and OS
X. (Laptop CPUs are usually relatively slower in 64-bit mode.)

So, for speed you may want to use a 32-bit build (especially on a
laptop), but to handle large datasets (and perhaps large files) a 64-bit
build. You can often build both and install them in the same place:
See Sub-architectures. (This is done for the Windows binary
distributions.)

Even on 64-bit builds of R there are limits on the size of R
objects (see help("Memory-limits"), some of which stem from the
use of 32-bit integers (especially in FORTRAN code). For example, the
dimensions of an array are limited to 2^{31} - 1.

9 The standalone Rmath library

The routines supporting the distribution and
special25 functions in R
and a few others are declared in C header file Rmath.h. These
can be compiled into a standalone library for linking to other
applications. (Note that they are not a separate library when R is
built, and the standalone version differs in several ways.)

The makefiles and other sources needed are in directory
src/nmath/standalone, so the following instructions assume that
is the current working directory (in the build directory tree on a
Unix-alike if that is separate from the sources).

Rmath.h contains ‘R_VERSION_STRING’, which is a character
string containing the current R version, for example "3.1.0".

There is full access to R’s handling of NaN, Inf and
-Inf via special versions of the macros and functions

ISNAN, R_FINITE, R_log, R_pow and R_pow_di

and (extern) constants R_PosInf, R_NegInf and NA_REAL.

There is no support for R’s notion of missing values, in particular
not for NA_INTEGER nor the distinction between NA and
NaN for doubles.

A little care is needed to use the random-number routines. You will
need to supply the uniform random number generator

double unif_rand(void)

or use the one supplied (and with a shared library or DLL you may
have to use the one supplied, which is the Marsaglia-multicarry with
an entry point

set_seed(unsigned int, unsigned int)

to set its seeds).

The facilities to change the normal random number generator are
available through the constant N01_kind. This takes values
from the enumeration type

9.1 Unix-alikes

If R has not already been made in the directory tree,
configure must be run as described in the main build
instructions.

Then (in src/nmath/standalone)

make

will make standalone libraries libRmath.a and libRmath.so
(libRmath.dylib on OS X): ‘make static’ and ‘make
shared’ will create just one of them.

To use the routines in your own C or C++ programs, include

#define MATHLIB_STANDALONE
#include <Rmath.h>

and link against ‘-lRmath’ (and ‘-lm’ if needed on your OS).
The example file test.c does nothing useful, but is provided to
test the process (via make test). Note that you will probably
not be able to run it unless you add the directory containing
libRmath.so to the LD_LIBRARY_PATH environment variable
(libRmath.dylib, DYLD_LIBRARY_PATH on OS X).

The targets

make install
make uninstall

will (un)install the header Rmath.h and shared and static
libraries (if built). Both prefix= and DESTDIR are
supported, together with more precise control as described for the main
build.

This creates a static library libRmath.a and a DLL
Rmath.dll. If you want an import library libRmath.dll.a
(you don’t need one), use

make -f Makefile.win shared implib

To use the routines in your own C or C++ programs using MinGW, include

#define MATHLIB_STANDALONE
#include <Rmath.h>

and link against ‘-lRmath’. This will use the first found of
libRmath.dll.a, libRmath.a and Rmath.dll in that
order, so the result depends on which files are present. You should be
able to force static or dynamic linking via

-Wl,-Bstatic -lRmath -Wl,dynamic
-Wl,-Bdynamic -lRmath

or by linking to explicit files (as in the ‘test’ target in
Makefile.win: this makes two executables, test.exe which
is dynamically linked, and test-static.exe, which is statically
linked).

It is possible to link to Rmath.dll using other compilers, either
directly or via an import library: if you make a MinGW import library as
above, you will create a file Rmath.def which can be used
(possibly after editing) to create an import library for other systems
such as Visual C++.

If you make use of dynamic linking you should use

#define MATHLIB_STANDALONE
#define RMATH_DLL
#include <Rmath.h>

to ensure that the constants like NA_REAL are linked correctly.
(Auto-import will probably work with MinGW, but it is better to be
sure. This is likely to also work with VC++, Borland and similar
compilers.)

Appendix A Essential and useful other programs under a Unix-alike

This appendix gives details of programs you will need to build R on
Unix-like platforms, or which will be used by R if found by
configure.

Remember that some package management systems (such as RPM and
Debian/Ubuntu’s) make a distinction between the user version of a
package and the development version. The latter usually has the same
name but with the extension ‘-devel’ or ‘-dev’: you need both
versions installed.

A.1 Essential programs and libraries

You need a means of compiling C and FORTRAN 90 (see Using FORTRAN). Your C compiler should be
ISO/IEC 6005927, POSIX 1003.1 and C99-compliant.28 R tries to choose suitable flags for
the C compilers it knows about, but you may have to set CC or
CFLAGS suitably. For recent versions of gcc with
glibc this means including
-std=gnu9929. If the compiler is detected as
gcc, -std=gnu99 will be appended to CC unless
it conflicts with a setting of CFLAGS. (Note that options
essential to run the compiler even for linking, such as those to set the
architecture, should be specified as part of CC rather than in
CFLAGS.)

Unless you do not want to view graphs on-screen (or use a Mac) you need
‘X11’ installed, including its headers and client libraries. For
recent Fedora distributions it means (at least) RPMs ‘libX11’,
‘libX11-devel’, ‘libXt’ and ‘libXt-devel’. On Debian we
recommend the meta-package ‘xorg-dev’. If you really do not want
these you will need to explicitly configure R without X11, using
--with-x=no.

The command-line editing (and command completion) depends on the
GNUreadline library: version 4.2 or later is needed
for all the features to be enabled. Otherwise you will need to
configure with --with-readline=no (or equivalent).

A suitably comprehensive iconv function is essential. The R
usage requires iconv to be able to translate between
"latin1" and "UTF-8", to recognize "" (as the
current encoding) and "ASCII", and to translate to and from the
Unicode wide-character formats "UCS-[24][BL]E" — this is true
by default for glibc30 but not of most commercial Unixes. However, you
can make use of GNUlibiconv (as used on OS X: see
https://www.gnu.org/software/libiconv/).

The OS needs to have enough support31 for wide-character
types: this is checked at configuration. A small number of POSIX
functions32 are essential, and others33 will be used if available.

A tar program is needed to unpack the sources and packages
(including the recommended packages). A version34 that can
automagically detect compressed archives is preferred for use with
untar(): the configure script looks for gtar and
gnutar before
tar – use environment variable TAR to override this.

There need to be suitable versions of the tools grep and
sed: the problems are usually with old AT&T and BSD variants.
configure will try to find suitable versions (including
looking in /usr/xpg4/bin which is used on some commercial
Unixes).

You will not be able to build most of the manuals unless you have
texi2any version 5.1 or later installed, and if not most of
the HTML manuals will be linked to a version on CRAN. To
make PDF versions of the manuals you will also need file
texinfo.tex installed (which is part of the GNUtexinfo distribution but is often made part of the TeX package
in re-distributions) as well as
texi2dvi.35
Further, the versions of texi2dvi and texinfo.tex need
to be compatible: we have seen problems with older TeX distributions.

The PDF documentation (including doc/NEWS.pdf) and building
vignettes needs pdftex and pdflatex. We require
LaTeX version 2005/12/01 or later (for UTF-8 support).
Building PDF package manuals (including the R reference manual) and
vignettes is sensitive to the version of the LaTeX package
hyperref and we recommend that the TeX distribution used is
kept up-to-date. A number of standard LaTeX packages are required
(including fancyvrb, url and some of the font packages such
as times, helvetic, ec and cm-super) and others
such as hyperref and inconsolata are desirable (and without
them you may need to change R’s defaults: see Making the manuals). Note that package hyperref (currently) requires
packages kvoptions, ltxcmds and refcount. For
distributions based on TeXLive the simplest approach may be to install
collections collection-latex, collection-fontsrecommended,
collection-latexrecommended, collection-fontsextra and
collection-latexextra (assuming they are not installed by
default): Fedora uses names like texlive-collection-fontsextra and
Debian/Ubuntu like texlive-fonts-extra.

If you want to build from the R Subversion repository then
texi2any is highly recommended as it is used to create files
in the tarball but not under Subversion.

The essential programs should be in your PATH at the time
configure is run: this will capture the full paths.

A.2 Useful libraries and programs

The ability to use translated messages makes use of gettext and
most likely needs GNUgettext: you do need this to work
with new translations, but otherwise the version contained in the R
sources will be used if no suitable external gettext is found.

The ‘modern’ version of the X11(), jpeg(), png()
and tiff() graphics devices uses the cairo and
(optionally) Pango libraries. Cairo version 1.2.0 or later is
required. Pango needs to be at least version 1.10, and 1.12 is the
earliest version we have tested. (For Fedora users we believe the
pango-devel RPM and its dependencies suffice.) R checks for
pkg-config, and uses that to check first that the
‘pangocairo’ package is installed (and if not, ‘cairo’) and if
additional flags are needed for the ‘cairo-xlib’ package, then if
suitable code can be compiled. These tests will fail if
pkg-config is not installed36, and are likely to fail if cairo was built
statically (unusual). Most systems with Gtk+ 2.8 or later
installed will have suitable libraries. OS X comes with none of these
libraries (but XQuartz, as used for 10.8 and later, ships cairo),
but cairo support (without Pango) has been added to the
binary distribution (see http://r.research.att.com/libs/ you need
fontconfig, freetype and pixman too):
pkg-config is still needed when building R from source and can
be installed from its sources.

For the best font experience with these devices you need suitable fonts
installed: Linux users will want the urw-fonts package. On
platforms which have it available, the msttcorefonts
package37 provides
TrueType versions of Monotype fonts such as Arial and Times New Roman.
Another useful set of fonts is the ‘liberation’ TrueType fonts available
at
https://fedorahosted.org/liberation-fonts/,38 which cover the Latin, Greek and Cyrillic alphabets
plus a fair range of signs. These share metrics with Arial, Times New
Roman and Courier New, and contain fonts rather similar to the first two
(https://en.wikipedia.org/wiki/Liberation_fonts). Then there
is the ‘Free UCS Outline Fonts’ project
(https://www.gnu.org/software/freefont/) which are
OpenType/TrueType fonts based on the URW fonts but with extended Unicode
coverage. See the R help on X11 on selecting such fonts.

The bitmapped graphics devices jpeg(), png() and
tiff() need the appropriate headers and libraries installed:
jpeg (version 6b or later, or libjpeg-turbo) or
libpng (version 1.2.7 or later) and zlib or libtiff
(any recent version – 3.9.[4567] and 4.0.[23] have been tested)
respectively. They also need support for either X11 or
cairo (see above). Should support for these devices not
be required or broken system libraries need to be avoided there are
configure options --without-libpng,
--without-jpeglib and --without-libtiff. For most
system installations the TIFF libraries will require JPEG libraries to
be present and perhaps linked explicitly, so --without-jpeglib
may also disable the tiff() device. The tiff() devices
only require a basic build of libtiff (not even JPEG support is
needed). Recent versions allow several other libraries to be linked
into libtiff such as lzma, jbig and jpeg12,
and these may need also to be present.

If you have them installed (including the appropriate headers and of
suitable versions), system versions of zlib (version 1.2.5 or
later),, libbz2 (version 1.0.6 or later: called
bzip2-libs/bzip2-devel or libbz2-1.0/libbz2-dev
by some Linux distributions) and PCRE (version 8.10 or later, preferably
8.32 or later39): will be used, otherwise versions in the R
sources will be compiled in. The external versions can be avoided by
configure options --without-system-zlib,
--without-system-bzlib and --without-system-pcre.

Option --with-system-tre is also available: it needs a recent
version of TRE. (The current sources are in the git repository
at https://github.com/laurikari/tre/, but at the time of writing
the resulting build will not pass its checks.).

Library liblzma from xz-utils version 5.0.3 or later
(including 5.2.x) will be used if installed: the version in the R
sources can be selected instead by configuring with
--without-system-xz. Systems differ in what they call the
package including this: e.g. on Fedora the library is in
‘xz-libs’ and the headers in ‘xz-devel’.

An implementation of XDR is required, and the R sources
contain one which is likely to suffice (although a system version may
have higher performance). XDR is part of RPC and
historically has been part of libc on a Unix-alike. However some
builds of glibc hide it with the intention that the
TI-RPC library be used instead, in which case libtirpc
(and its development version) needs to be installed, and its headers
need to be on the C include path or in /usr/include/tirpc.

Use of the X11 clipboard selection requires the Xmu headers and
libraries. These are normally part of an X11 installation (e.g. the
Debian meta-package ‘xorg-dev’), but some distributions have split
this into smaller parts, so for example recent versions of Fedora
require the ‘libXmu’ and ‘libXmu-devel’ RPMs.

Some systems (notably OS X and at least some FreeBSD systems) have
inadequate support for collation in multibyte locales. It is possible
to replace the OS’s collation support by that from ICU (International
Components for Unicode, http://site.icu-project.org/), and this
provides much more precise control over collation on all systems. ICU
is available as sources and as binary distributions for (at least) most
Linux distributions, Solaris, FreeBSD and AIX, usually as libicu
or icu4c. It will be used by default where available (including
on OS X >= 10.4): should a very old or broken version of ICU be found
this can be suppressed by --without-ICU.

If libcurl version 7.28.0 or later is available (including its
development files), it will be linked in to support
curlGetHeaders and the "libcurl" methods of
download.file and url. This is recommended as it gives
access to ‘https://’ and ‘ftps://’ URLs. Information on
libcurl is found from the curl-config script: if that
is missing or needs to be overridden40
there are macros described in file config.site.

The bitmap and dev2bitmap devices and function
embedFonts() use ghostscript
(http://www.ghostscript.com/). This should either be in your
path when the command is run, or its full path specified by the
environment variable R_GSCMD at that time.

A.2.1 Tcl/Tk

The tcltk package needs Tcl/Tk >= 8.4 installed: the sources are
available at https://www.tcl.tk/. To specify the locations of the
Tcl/Tk files you may need the configuration options

--with-tcltk

use Tcl/Tk, or specify its library directory

--with-tcl-config=TCL_CONFIG

specify location of tclConfig.sh

--with-tk-config=TK_CONFIG

specify location of tkConfig.sh

or use the configure variables TCLTK_LIBS and
TCLTK_CPPFLAGS to specify the flags needed for linking against
the Tcl and Tk libraries and for finding the tcl.h and
tk.h headers, respectively. If you have both 32- and 64-bit
versions of Tcl/Tk installed, specifying the paths to the correct config
files may be necessary to avoid confusion between them.

Versions of Tcl/Tk up to 8.5.12 and 8.6.0 have been tested (including
most versions of 8.4.x, but not recently).

A.2.2 Java support

The build process looks for Java support on the host system, and if it
finds it sets some settings which are useful for Java-using packages.
JAVA_HOME can be set to point to a specific JRE/JDK.

Principal amongst these are setting some library paths to the Java
libraries and JVM, which are stored in environment variable
R_JAVA_LD_LIBRARY_PATH in file R_HOME/etc/ldpaths (or
a sub-architecture-specific version). A typical setting for
‘x86_64’ Linux is

Note that this unfortunately depends on the exact version of the JRE/JDK
installed, and so may need updating if the Java installation is updated.
This can be done by running R CMD javareconf which updates
settings in both etc/Makeconf and
R_HOME/etc/ldpaths. See R CMD javareconf --help for
details.

Another way of overriding those settings is to set the environment variable
R_JAVA_LD_LIBRARY_PATH (before R is started, hence not in
~/.Renviron), which suffices to run already-installed
Java-using packages. For example

R_JAVA_LD_LIBRARY_PATH=/usr/lib/jvm/java-1.7.0/jre/lib/amd64/server

It may be possible to avoid this by specifying an invariant link as the
path. For example, on that system either of

A.2.3 Other compiled languages

Some add-on packages need a C++ compiler. This is specified by the
configure variables CXX, CXXFLAGS and similar.
configure will normally find a suitable compiler. However, in
most cases this will be a C++98 compiler, and as from R 3.1.0 it is
possible to specify an alternative compiler for use with C++11 by the
configure variables CXX1X, CXX1XSTD, CXX1XFLAGS and
similar. Again, configure will normally find a suitable value
for CXX1XSTD if the compiler given by CXX is capable of
compiling C++11 code, but it is possible that a completely different
compiler will be needed (it is for OS X < 10.9 and Solaris, for
example).

Other packages need full Fortran 90 (or later) support. For source
files with extension .f90 or .f95, the compiler defined by
the macro FC is used by R CMD INSTALL. This is found
when R is configured and is often the same as F77: note that
it is detected by the name of the command without a test that it can
actually compile Fortran 90 code. Set the configure variable FC
to override this if necessary: variables FCFLAGS,
FCPICFLAGS, FCLIBS, SHLIB_FCLD and
SHLIB_FCLDFLAGS might also need to be set.

See file config.site in the R source for more details about
these variables.

A.3 Linear algebra

A.3.1 BLAS

The linear algebra routines in R can make use of enhanced
BLAS (Basic Linear Algebra Subprograms,
http://www.netlib.org/blas/faq.html) routines. However,
these have to be explicitly requested at configure time: R provides
an internal BLAS which is well-tested and will be adequate for
most uses of R.

You can specify a particular BLAS library via a value
for the configuration option --with-blas and not to use an
external BLAS library by --without-blas (the
default). If --with-blas is given with no =, its value
is taken from the
environment variable BLAS_LIBS, set for example in
config.site. If neither the option nor the environment variable
supply a value, a search is made for a suitable BLAS. If the
value is not obviously a linker command (starting with a dash or giving
the path to a library), it is prefixed by ‘-l’, so

--with-blas="foo"

is an instruction to link against ‘-lfoo’ to find an external
BLAS (which needs to be found both at link time and run time).

The configure code checks that the external BLAS is complete
(it must include all double precision and double complex routines, as
well as LSAME), and appears to be usable. However, an external
BLAS has to be usable from a shared object (so must contain
position-independent code), and that is not checked.

Some enhanced BLASes are compiler-system-specific
(sunperf on Solaris41, libessl on IBM,
Accelerate on OS X). The correct incantation for
these is usually found via--with-blas with no value on
the appropriate platforms.

Some of the external BLASes are multi-threaded. One issue is
that R profiling (which uses the SIGPROF signal) may cause
problems, and you may want to disable profiling if you use a
multi-threaded BLAS. Note that using a multi-threaded
BLAS can result in taking more CPU time and even
more elapsed time (occasionally dramatically so) than using a similar
single-threaded BLAS. On a machine running other tasks, there
can be contention for CPU caches that reduces the effectiveness of the
optimization of cache use by a BLAS implementation.

Note that under Unix (but not under Windows) if R is compiled against
a non-default BLAS and --enable-BLAS-shlib is
not used, then all BLAS-using packages must also be.
So if R is re-built to use an enhanced BLAS then packages
such as quantreg will need to be re-installed.

R relies on ISO/IEC 60559 compliance of an
external BLAS. This can be broken if for example the code
assumes that terms with a zero factor are always zero and do not need to
be computed—whereas x*0 can be NaN. This is checked in
the test suite.

External BLAS implementations often make less use of
extended-precision floating-point registers and will almost certainly
re-order computations. This can result in less accuracy than using the
internal BLAS, and may result in different solutions, e.g.
different signs in SVD and eigendecompositions.

The URIs for several of these BLAS are subject to frequent gratuitous
changes, so you will need to search for their current locations.

A.3.1.1 ATLAS

ATLAS (http://math-atlas.sourceforge.net/) is a “tuned”
BLAS that runs on a wide range of Unix-alike platforms.
Unfortunately it is built by default as a static library that on some
platforms cannot be used with shared objects such as are used in R
packages. Be careful when using pre-built versions of ATLAS (they seem
to work on ‘ix86’ platforms, but not always on ‘x86_64’
ones).

The usual way to specify ATLAS will be via

--with-blas="-lf77blas -latlas"

if the libraries are in the library path, otherwise by

--with-blas="-L/path/to/ATLAS/libs -lf77blas -latlas"

For example, ‘x86_64’ Fedora needs

--with-blas="-L/usr/lib64/atlas -lf77blas -latlas"

For systems with multiple CPU cores it is possible to use a
multi-threaded version of ATLAS, by specifying

--with-blas="-lptf77blas -lpthread -latlas"

Consult its installation guide for how to build ATLAS with
position-independent code, and as a shared library.

A.3.1.2 ACML

For ‘x86_64’ processors42 under Linux there is the AMD Core Math Library (ACML).
For the gcc version we could use

--with-blas="-lacml"

if the appropriate library directory (such as
/opt/acml5.1.0/gfortran64/lib) is in the LD_LIBRARY_PATH.
For other compilers, see the ACML documentation. There is a
multithreaded Linux version of ACML available for recent versions of
gfortran. To make use of this you will need something like

--with-blas="-L/opt/acml5.1.0/gfortran64_mp/lib -lacml_mp"

(and you may need to arrange for the directory to be in ld.so
cache).

See see Shared BLAS for an alternative (and in many ways preferable)
way to use ACML.

The version last tested (5.1.0) failed the reg-BLAS.R test in its
handling of NAs.

A.3.1.3 Goto and OpenBLAS

Dr Kazushige Goto wrote a tuned BLAS for several processors and
OSes, which was frozen in mid-2010. The final version is known as
GotoBLAS2, and was re-released under a much less restrictive licence.
Once it is built and installed, it can be used by configuring R with

--with-blas="-lgoto2"

See see Shared BLAS for an alternative (and in many ways preferable)
way to use it.

OpenBLAS (http://www.openblas.net/) is a descendant
project with support for some later CPUs (e.g. Intel Sandy Bridge).
Once installed it can be used by something like

A.3.1.4 Intel MKL

For Intel processors, and perhaps others, and some distributions of
Linux, there is Intel’s Math Kernel Library. You are strongly
encouraged to read the MKL User’s Guide, which is installed with the
library, before attempting to link to MKL. There are also versions of
MKL for OS X and Windows, but they did not work with the standard
compilers used for R on those platforms.

The MKL interface has changed several times, and may change again: the
following notes apply exactly only to version 10.3 but have been used
with version 11.1.

Versions 10 and later of MKL support two linking models. Only the
layered model is described here as it gives the user fine-grained
control over four different library layers: interface, threading,
computation, and run-time library support. The choice of interface
layer is important on ‘x86_64’ since the Intel Fortran compiler
returns complex values in different registers from the GNU
Fortran compiler: you must therefore use the interface layer that
matches your compiler (mkl_intel* or mkl_gf*).

where some versions may need -lmkl_lapack before
-lmkl_core. The order of the libraries is important. The option
--with-lapack is used since MKL contains a tuned copy of LAPACK
as well as BLAS (see LAPACK), although this can be
omitted.

Threaded MKL may be used (according to Zhang Zhang of Intel) by
replacing the line defining the variable MKL with (Intel OMP)

The default number of threads will be chosen by the OpenMP software, but
can be controlled by setting OMP_NUM_THREADS or
MKL_NUM_THREADS, and in recent versions seems to default to a
sensible value for sole use of the machine.

A.3.1.5 Shared BLAS

The BLAS library will be used for many of the add-on packages
as well as for R itself. This means that it is better to use a
shared/dynamic BLAS library, as most of a static library will
be compiled into the R executable and each BLAS-using
package.

R offers the option of compiling the BLAS into a dynamic
library libRblas stored in R_HOME/lib and linking
both R itself and all the add-on packages against that library.

This is the default on all platforms except AIX unless an external
BLAS is specified and found: for the latter it can be used by
specifying the option --enable-BLAS-shlib, and it can always be
disabled via --disable-BLAS-shlib.

This has both advantages and disadvantages.

It saves space by having only a single copy of the BLAS
routines, which is helpful if there is an external static BLAS
such as used to be standard for ATLAS.

There may be performance disadvantages in using a shared BLAS.
Probably the most likely is when R’s internal BLAS is used
and R is not built as a shared library, when it is possible to
build the BLAS into R.bin (and libR.a) without
using position-independent code. However, experiments showed that in
many cases using a shared BLAS was as fast, provided high
levels of compiler optimization are used.

It is easy to change the BLAS without needing to re-install
R and all the add-on packages, since all references to the
BLAS go through libRblas, and that can be replaced.
Note though that any dynamic libraries the replacement links to will
need to be found by the linker: this may need the library path to be
changed in R_HOME/etc/ldpaths.

Another option to change the BLAS in use is to symlink a
dynamic BLAS library (such as ACML or Goto’s) to
R_HOME/lib/libRblas.so. For example, just

will change the BLAS in use to multithreaded ACML. A similar
link works for some versions of Goto BLAS, OpenBLAS and MKL
(provided the appropriate lib directory is in the run-time
library path or ld.so cache).

A.3.2 LAPACK

Provision is made for using an external LAPACK library, principally to
cope with BLAS libraries which contain a copy of LAPACK (such
as sunperf on Solaris, Accelerate on OS X and ACML and MKL
on ‘ix86’/‘x86_64’ Linux). At least LAPACK version 3.2
is required. This can only be done if --with-blas has been used.

However, the likely performance gains are thought to be small (and may
be negative), and the default is not to search for a suitable LAPACK
library, and this is definitely not recommended. You can
specify a specific LAPACK library or a search for a generic library by
the configuration option --with-lapack. The default for
--with-lapack is to check the BLAS library and then
look for an external library ‘-llapack’. Sites searching for the
fastest possible linear algebra may want to build a LAPACK library using
the ATLAS-optimized subset of LAPACK. To do so specify something like

--with-lapack="-L/path/to/ATLAS/libs -llapack -lcblas"

since the ATLAS subset of LAPACK depends on libcblas. A value
for --with-lapack can be set via the environment
variable
LAPACK_LIBS, but this will only be used if --with-lapack
is specified (as the default value is no) and the BLAS library
does not contain LAPACK.

Since ACML contains a full LAPACK, if selected as the BLAS it
can be used as the LAPACK via--with-lapack.

If you do use --with-lapack, be aware of potential problems
with bugs in the LAPACK sources (or in the posted corrections to those
sources). In particular, bugs in DGEEV and DGESDD have
resulted in error messages such as

DGEBRD gave error code -10

. Other potential problems are incomplete versions of the libraries,
seen several times in Linux distributions over the years.

Please do bear in mind that using --with-lapack is
‘definitely not recommended’: it is provided only
because it is necessary on some platforms and because some users want to
experiment with claimed performance improvements. Reporting problems
where it is used unnecessarily will simply irritate the R helpers.

Note too the comments about ISO/IEC 60559
compliance in the section of external BLAS: these apply
equally to an external LAPACK, and for example the Intel MKL
documentation says

LAPACK routines assume that input matrices do not contain IEEE 754
special values such as INF or NaN values. Using these special values may
cause LAPACK to return unexpected results or become unstable.

We rely on limited support in LAPACK for matrices with 2^{31} or
more elements: it is quite possible that an external LAPACK will not
have that support.

If you have a pure FORTRAN 77 compiler which cannot compile LAPACK it
may be possible to use CLAPACK from
http://www.netlib.org/clapack/ by something like

-with-lapack="-lclapack -lf2c"

provided these were built with position-independent code and the calling
conventions for double complex function return values match those in the
BLAS used, so it may be simpler to use CLAPACK built to use CBLAS and

A.3.3 Caveats

As with all libraries, you need to ensure that they and R were
compiled with compatible compilers and flags. For example, this has
meant that on Sun Sparc using the native compilers the flag
-dalign is needed if sunperf is to be used.

On some systems it is necessary that an external BLAS/LAPACK
was built with the same FORTRAN compiler used to build R: known
problems are with R built with gfortran, see Using gfortran.

B.1 Configuration options

will give a list. Probably the most important ones not covered
elsewhere are (defaults in brackets)

--with-x

use the X Window System [yes]

--x-includes=DIR

X include files are in DIR

--x-libraries=DIR

X library files are in DIR

--with-readline

use readline library (if available) [yes]

--enable-R-profiling

attempt to compile support for Rprof() [yes]

--enable-memory-profiling

attempt to compile support for Rprofmem() and tracemem() [no]

--enable-R-shlib

build R as a shared/dynamic library [no]

--enable-BLAS-shlib

build the BLAS as a shared/dynamic library [yes, except on AIX]

You can use --without-foo or --disable-foo for the
negatives.

You will want to use --disable-R-profiling if you are building
a profiled executable of R (e.g. with ‘-pg)’.

Flag --enable-R-shlib causes the make process to build R as
a dynamic (shared) library, typically called libR.so, and link
the main R executable R.bin against that library. This can
only be done if all the code (including system libraries) can be
compiled into a dynamic library, and there may be a
performance43 penalty. So you probably
only want this if you will be using an application which embeds R.
Note that C code in packages installed on an R system linked with
--enable-R-shlib is linked against the dynamic library and so
such packages cannot be used from an R system built in the default
way. Also, because packages are linked against R they are on some
OSes also linked against the dynamic libraries R itself is linked
against, and this can lead to symbol conflicts.

For maximally effective use of valgrind, R should be
compiled with valgrind instrumentation. The configure option
is --with-valgrind-instrumentation=level, where
level is 0, 1 or 2. (Level 0 is the default and does not add
any anything.) The system headers for valgrind can be
requested by option --with-system-valgrind-headers: they will
be used if present (on Linux they may be in a separate package such as
valgrind-devel). Note though that there is no guarantee that the
code in R will be compatible with future valgrind headers.

If you need to re-configure R with different options you may need to run
make clean or even make distclean before doing so.

The configure script has other generic options added by
autoconf and which are not supported for R: in particular
building for one architecture on a different host is not possible.

B.2 Internationalization support

Translation of messages is supported via GNUgettext
unless disabled by the configure option --disable-nls.
The configure report will show NLS as one of the
‘Additional capabilities’ if support has been compiled in, and running
in an English locale (but not the C locale) will include

B.3 Configuration variables

If you need or want to set certain configure variables to something
other than their default, you can do that by either editing the file
config.site (which documents many of the variables you might want
to set: others can be seen in file etc/Renviron.in) or on the
command line as

./configure VAR=value

If you are building in a directory different from the sources, there can
be copies of config.site in the source and the build directories,
and both will be read (in that order). In addition, if there is a file
~/.R/config, it is read between the config.site files in
the source and the build directories.

There is also a general autoconf mechanism for
config.site files, which are read before any of those mentioned
in the previous paragraph. This looks first at a file specified by the
environment variable CONFIG_SITE, and if not is set at files such
as /usr/local/share/config.site and
/usr/local/etc/config.site in the area (exemplified by
/usr/local) where R would be installed.

These variables are precious, implying that they do not have to
be exported to the environment, are kept in the cache even if not
specified on the command line, checked for consistency between two
configure runs (provided that caching is used), and are kept during
automatic reconfiguration as if having been passed as command line
arguments, even if no cache is used.

See the variable output section of configure --help for a list of
all these variables.

If you find you need to alter configure variables, it is worth noting
that some settings may be cached in the file config.cache, and it
is a good idea to remove that file (if it exists) before re-configuring.
Note that caching is turned off by default: use the command line
option --config-cache (or -C) to enable caching.

B.3.1 Setting paper size

One common variable to change is R_PAPERSIZE, which defaults to
‘a4’, not ‘letter’. (Valid values are ‘a4’,
‘letter’, ‘legal’ and ‘executive’.)

This is used both when configuring R to set the default, and when
running R to override the default. It is also used to set the
paper size when making PDF manuals.

The configure default will most often be ‘a4’ if R_PAPERSIZE
is unset. (If the (Debian Linux) program paperconf is found
or the environment variable PAPERSIZE is set, these are used to
produce the default.)

B.3.3 Compilation flags

If you have libraries and header files, e.g., for GNU
readline, in non-system directories, use the variables LDFLAGS
(for libraries, using ‘-L’ flags to be passed to the linker) and
CPPFLAGS (for header files, using ‘-I’ flags to be passed to
the C/C++ preprocessors), respectively, to specify these locations.
These default to ‘-L/usr/local/lib’ (LDFLAGS,
‘-L/usr/local/lib64’ on most 64-bit Linux OSes) and
‘-I/usr/local/include’ (CPPFLAGS) to catch the most common
cases. If libraries are still not found, then maybe your
compiler/linker does not support re-ordering of -L and
-l flags (this has been reported to be a problem on HP-UX with
the native cc). In this case, use a different compiler (or a
front end shell script which does the re-ordering).

These flags can also be used to build a faster-running version of R.
On most platforms using gcc, having ‘-O3’ in
CFLAGS and FFLAGS produces worthwhile performance gains
with gcc and gfortran, but may result in a less
reliable build (both segfaults and incorrect numeric computations have
been seen). On systems using the GNU linker (especially those
using R as a shared library), it is likely that including
‘-Wl,-O1’ in LDFLAGS is worthwhile, and
‘'-Bdirect,--hash-style=both,-Wl,-O1'’ is recommended at
https://lwn.net/Articles/192624/. Tuning compilation to a
specific CPU family (e.g. ‘-mtune=native’ for
gcc) can give worthwhile performance gains, especially on
older architectures such as ‘ix86’.

B.3.4 Making manuals

B.4 Setting the shell

By default the shell scripts such as R will be ‘#!/bin/sh’
scripts (or using the SHELL chosen by configure). This is
almost always satisfactory, but on a few systems /bin/sh is not a
Bourne shell or clone, and the shell to be used can be changed by
setting the configure variable R_SHELL to a suitable value (a full
path to a shell, e.g. /usr/local/bin/bash).

B.5 Using make

To compile R, you will most likely find it easiest to use
GNUmake, although the Sun make works on
Solaris, as does the native FreeBSD make. The native
make has been reported to fail on SGI Irix 6.5 and Alpha/OSF1
(aka Tru64).

To build in a separate directory you need a make that uses the
VPATH variable, for example GNUmake, or Sun
make on Solaris 7 or later.

dmake has also been used. e.g, on Solaris 10.

If you want to use a make by another name, for example if your
GNUmake is called ‘gmake’, you need to set the
variable MAKE at configure time, for example

B.6 Using FORTRAN

To compile R, you need a FORTRAN compiler. The default
is to search for
f95, fort, xlf95,
ifort, ifc, efc, pgf95lf95, gfortran, ftn, g95,
f90, xlf90, pghpf, pgf90,
epcf90,
g77, f77, xlf, frt,
pgf77, cf77, fort77, fl32,
af77 (in that order)44, and use whichever is found first; if none is found,
R cannot be compiled.
However, if CC is gcc, the matching FORTRAN compiler
(g77 for gcc 3 and gfortran for
gcc 4) is used if available.

The search mechanism can be changed using the configure variable
F77 which specifies the command that runs the FORTRAN 77
compiler. If your FORTRAN compiler is in a non-standard location, you
should set the environment variable PATH accordingly before
running configure, or use the configure variable F77 to
specify its full path.

If your FORTRAN libraries are in slightly peculiar places, you should
also look at LD_LIBRARY_PATH or your system’s equivalent to make
sure that all libraries are on this path.

Note that only FORTRAN compilers which convert identifiers to lower case
are supported.

You must set whatever compilation flags (if any) are needed to ensure
that FORTRAN integer is equivalent to a C int pointer and
FORTRAN double precision is equivalent to a C double
pointer. This is checked during the configuration process.

Some of the FORTRAN code makes use of COMPLEX*16 variables, which
is a Fortran 90 extension. This is checked for at configure
time45, but you may need to avoid
compiler flags asserting FORTRAN 77 compliance.

Compiling the version of LAPACK in the R sources also requires some
Fortran 90 extensions, but these are not needed if an external LAPACK is
used.

It might be possible to use f2c, the FORTRAN-to-C converter
(http://www.netlib.org/f2c), via a script. (An example script
is given in scripts/f77_f2c: this can be customized by setting
the environment variables F2C, F2CLIBS, CC and
CPP.) You will need to ensure that the FORTRAN type
integer is translated to the C type int. Normally
f2c.h contains ‘typedef long int integer;’, which will work
on a 32-bit platform but needs to be changed to ‘typedef int
integer;’ on a 64-bit platform. If your compiler is not gcc
you will need to set
FPICFLAGS appropriately. Also, the included LAPACK sources
contain constructs that f2c is unlikely to be able to process,
so you would need to use an external LAPACK library (such as CLAPACK
from http://www.netlib.org/clapack/).

B.6.1 Using gfortran

gfortran is the F95 compiler that is part of
gcc 4.x.y.

On Linux ‘x86_64’ systems there is an incompatibility in the
return conventions for double-complex functions between
gfortran and g77 which results in the final example
in example(eigen) hanging or segfaulting under external
BLASs built under g77 (and also some external
LAPACKs). The commonest cases will be detected by a configure
test. Although g77 is long obsolete this is still sometimes
seen with C versions of external software using g77
conventions.

The default FFLAGS and FCFLAGS chosen (by
autoconf) for a GNU FORTRAN compiler is ‘-g
-O2’. This has caused problems (segfaults and infinite loops) on
‘x86_64’ Linux in the past, but seems fine with
gfortran 4.4.4 and later: for gfortran 4.3.x set
FFLAGS and FCFLAGS to use at most ‘-O’.

B.7 Compile and load flags

A wide range of flags can be set in the file config.site or as
configure variables on the command line. We have already mentioned

CPPFLAGS

header file search directory (-I) and any other miscellaneous
options for the C and C++ preprocessors and compilers

LDFLAGS

path (-L), stripping (-s) and any other miscellaneous
options for the linker

and others include

CFLAGS

debugging and optimization flags, C

MAIN_CFLAGS

ditto, for compiling the main program

SHLIB_CFLAGS

for shared objects

FFLAGS

debugging and optimization flags, FORTRAN

SAFE_FFLAGS

ditto for source files which need exact floating point behaviour

MAIN_FFLAGS

ditto, for compiling the main program

SHLIB_FFLAGS

for shared objects

MAIN_LDFLAGS

additional flags for the main link

SHLIB_LDFLAGS

additional flags for linking the shared objects

LIBnn

the primary library directory, lib or lib64

CPICFLAGS

special flags for compiling C code to be turned into a shared object

FPICFLAGS

special flags for compiling Fortran code to be turned into a shared object

CXXPICFLAGS

special flags for compiling C++ code to be turned into a shared object

FCPICFLAGS

special flags for compiling Fortran 95 code to be turned into a shared object

DEFS

defines to be used when compiling C code in R itself

Library paths specified as -L/lib/path in LDFLAGS are
collected together and prepended to LD_LIBRARY_PATH (or your
system’s equivalent), so there should be no need for -R or
-rpath flags.

Variables such as CPICFLAGS are determined where possible by
configure. Some systems allows two types of PIC flags, for
example ‘-fpic’ and ‘-fPIC’, and if they differ the first
allows only a limited number of symbols in a shared object. Since R
as a shared library has about 6200 symbols, if in doubt use the larger
version.

To compile a profiling version of R, one might for example want to
use ‘MAIN_CFLAGS=-pg’, ‘MAIN_FFLAGS=-pg’,
‘MAIN_LDFLAGS=-pg’ on platforms where ‘-pg’ cannot be used
with position-independent code.

Beware: it may be necessary to set CFLAGS and
FFLAGS in ways compatible with the libraries to be used: one
possible issue is the alignment of doubles, another is the way
structures are passed.

On some platforms configure will select additional flags for
CFLAGS, CPPFLAGS, FFLAGS, CXXFLAGS and
LIBS in R_XTRA_CFLAGS (and so on). These are for options
which are always required, for example to force IEC 60559
compliance.

B.8 Maintainer mode

There are several files that are part of the R sources but can be
re-generated from their own sources by configuring with option
--enable-maintainer-mode and then running make in the
build directory. This requires other tools to be installed, discussed
in the rest of this section.

File configure is created from configure.ac and the files
under m4 by autoconf and aclocal. There is a
formal version requirement on autoconf of 2.62 or later, but
it is unlikely that anything other than the most recent versions have
been thoroughly tested.

File src/include/config.h is created by autoheader.

Grammar files *.y are converted to C sources by an implementation
of yacc, usually bison -y: these are found in
src/main and src/library/tools/src. It is known that
earlier versions of bison generate code which reads (and in
some cases writes) outside array bounds: bison 2.6.1 was found
to be satisfactory.

The ultimate sources for package compiler are in its noweb
directory. To re-create the sources from
src/library/compiler/noweb/compiler.nw, the command
notangle is required. This is likely to need to be installed
from the sources at https://www.cs.tufts.edu/~nr/noweb/ (and can
also be found on CTAN). The package sources are only re-created even in
maintainer mode if src/library/compiler/noweb/compiler.nw has
been updated.

It is likely that in future creating configure will need the GNU
‘autoconf archive’ installed. This can be found at
https://www.gnu.org/software/autoconf-archive/ and as a package
(usually called autoconf-archive) in most packaged distributions,
for example Debian, Fedora, OpenCSW, Homebrew and MacPorts.

Appendix C Platform notes

This section provides some notes on building R on different Unix-alike
platforms. These notes are based on tests run on one or two systems in
each case with particular sets of compilers and support libraries.
Success in building R depends on the proper installation and functioning
of support software; your results may differ if you have other versions
of compilers and support libraries.

Older versions of this manual (for R < 2.10.0) contain notes on
platforms such as HP-UX, IRIX and Alpha/OSF1 for which we have had no
recent reports.

C macros to select particular platforms can be tricky to track down
(there is a fair amount of misinformation on the Web). The Wiki
(currently) at http://sourceforge.net/p/predef/wiki/Home/ can be
helpful. The R sources currently use

C.1 X11 issues

The ‘X11()’ graphics device is the one started automatically on
Unix-alikes when plotting. As its name implies, it displays on a (local
or remote) X server, and relies on the services provided by the X
server.

The ‘modern’ version of the ‘X11()’ device is based on ‘cairo’
graphics and (in most implementations) uses ‘fontconfig’ to pick and
render fonts. This is done on the server, and although there can be
selection issues, they are more amenable than the issues with
‘X11()’ discussed in the rest of this section.

When X11 was designed, most displays were around 75dpi, whereas today
they are of the order of 100dpi or more. If you find that X11()
is reporting46 missing font sizes, especially larger ones, it is likely
that you are not using scalable fonts and have not installed the 100dpi
versions of the X11 fonts. The names and details differ by system, but
will likely have something like Fedora’s

and you need to ensure that the ‘-100dpi’ versions are installed
and on the X11 font path (check via xset -q). The
‘X11()’ device does try to set a pointsize and not a pixel size:
laptop users may find the default setting of 12 too large (although very
frequently laptop screens are set to a fictitious dpi to appear like a
scaled-down desktop screen).

More complicated problems can occur in non-Western-European locales, so
if you are using one, the first thing to check is that things work in
the C locale. The likely issues are a failure to find any fonts
or glyphs being rendered incorrectly (often as a pair of ASCII
characters). X11 works by being asked for a font specification and
coming up with its idea of a close match. For text (as distinct from
the symbols used by plotmath), the specification is the first element of
the option "X11fonts" which defaults to

"-adobe-helvetica-%s-%s-*-*-%d-*-*-*-*-*-*-*"

If you are using a single-byte encoding, for example ISO 8859-2 in
Eastern Europe or KOI8-R in Russian, use xlsfonts to find an
appropriate family of fonts in your encoding (the last field in the
listing). If you find none, it is likely that you need to install
further font packages, such as ‘xorg-x11-fonts-ISO8859-2-75dpi’ and
‘xorg-x11-fonts-cyrillic’ shown in the listing above.

Multi-byte encodings (most commonly UTF-8) are even more complicated.
There are few fonts in ‘iso10646-1’, the Unicode encoding, and they
only contain a subset of the available glyphs (and are often fixed-width
designed for use in terminals). In such locales fontsets are
used, made up of fonts encoded in other encodings. If the locale you
are using has an entry in the ‘XLC_LOCALE’ directory (typically
/usr/share/X11/locale, it is likely that all you need to do is to
pick a suitable font specification that has fonts in the encodings
specified there. If not, you may have to get hold of a suitable locale
entry for X11. This may mean that, for example, Japanese text can be
displayed when running in ‘ja_JP.UTF-8’ but not when running in
‘en_GB.UTF-8’ on the same machine (although on some systems many
UTF-8 X11 locales are aliased to ‘en_US.UTF-8’ which covers several
character sets, e.g. ISO 8859-1 (Western European), JISX0208 (Kanji),
KSC5601 (Korean), GB2312 (Chinese Han) and JISX0201 (Kana)).

On some systems scalable fonts are available covering a wide range of
glyphs. One source is TrueType/OpenType fonts, and these can provide
high coverage. Another is Type 1 fonts: the URW set of Type 1 fonts
provides standard typefaces such as Helvetica with a larger coverage of
Unicode glyphs than the standard X11 bitmaps, including Cyrillic. These
are generally not part of the default install, and the X server may need
to be configured to use them. They might be under the X11 fonts
directory or elsewhere, for example,

C.2 Linux

Linux is the main development platform for R, so compilation from the
sources is normally straightforward with the standard compilers.

Remember that some package management systems (such as RPM and
deb) make a distinction between the user version of a package and the
developer version. The latter usually has the same name but with the
extension ‘-devel’ or ‘-dev’: you need both versions
installed. So please check the configure output to see if the
expected features are detected: if for example ‘readline’ is
missing add the developer package. (On most systems you will also need
‘ncurses’ and its developer package, although these should be
dependencies of the ‘readline’ package(s).) You should expect to
see in the configure summary

When R has been installed from a binary distribution there are
sometimes problems with missing components such as the FORTRAN
compiler. Searching the ‘R-help’ archives will normally reveal
what is needed.

It seems that ‘ix86’ Linux accepts non-PIC code in shared
libraries, but this is not necessarily so on other platforms, in
particular on 64-bit CPUs such as ‘x86_64’. So care
can be needed with BLAS libraries and when building R as a
shared library to ensure that position-independent code is used in any
static libraries (such as the Tcl/Tk libraries, libpng,
libjpeg and zlib) which might be linked against.
Fortunately these are normally built as shared libraries with the
exception of the ATLAS BLAS libraries.

The default optimization settings chosen for CFLAGS etc are
conservative. It is likely that using -mtune will result in
significant performance improvements on recent CPUs (especially for
‘ix86’): one possibility is to add -mtune=native for
the best possible performance on the machine on which R is being
installed: if the compilation is for a site-wide installation, it may
still be desirable to use something like
-mtume=core2.47 It is also possible to increase the
optimization levels to -O3: however for many versions of the
compilers this has caused problems in at least one CRAN
package.

For platforms with both 64- and 32-bit support, it is likely that

LDFLAGS="-L/usr/local/lib64 -L/usr/local/lib"

is appropriate since most (but not all) software installs its 64-bit
libraries in /usr/local/lib64. To build a 32-bit version of R
on ‘x86_64’ with Fedora 18 we used

Note the use of ‘LIBnn’: ‘x86_64’ Fedora installs its
64-bit software in /usr/lib64 and 32-bit software in
/usr/lib. Linking will skip over inappropriate binaries, but for
example the 32-bit Tcl/Tk configure scripts are in /usr/lib. It
may also be necessary to set the pkg-config path, e.g. by

export PKG_CONFIG_PATH=/usr/local/lib/pkgconfig:/usr/lib/pkgconfig

64-bit versions of Linux are built with support for files > 2Gb, and
32-bit versions will be if possible unless --disable-largefile
is specified.

To build a 64-bit version of R on ‘ppc64’ (also known as
‘powerpc64’) with gcc 4.1.1, Ei-ji Nakama used

C.2.1 Clang

R has been built with Linux ‘ix86’ and ‘x86_64’ C and
C++ compilers (http://clang.llvm.org) based on the Clang
front-ends, invoked by CC=clang CXX=clang++, together with
gfortran. These take very similar options to the
corresponding GCC compilers.

This has to be used in conjunction with a Fortran compiler: the
configure code will remove -lgcc from FLIBS,
which is needed for some versions of gfortran.

The current default for clang++ is to use the C++ runtime from
the installed g++. Using the runtime from the libc++
project (http://libcxx.llvm.org/) has also been tested: for some
R packages only the variant using libcxxabi was successful.

configure will add ‘-c99’ to CC for
C99-compliance. This causes warnings with icc 10 and later, so
use CC="icc -std=c99" there. The flag -wd188 suppresses
a large number of warnings about the enumeration type ‘Rboolean’.
Because the Intel C compiler sets ‘__GNUC__’ without complete
emulation of gcc, we suggest adding CPPFLAGS=-no-gcc.

To maintain correct IEC 60559 arithmetic you most likely
need add flags to CFLAGS, FFLAGS and CXXFLAGS such
as -mp (shown above) or -fp-model precise -fp-model
source, depending on the compiler version.

C.3 OS X

You can build R using Apple’s ‘Command Line Tools’ and suitable
compilers. You will also need readline (or to configure with
--without-readline), and a Fortran compiler. Those and other
binary components are available from
http://r.research.att.com/libs.

You may also need to install an X sub-system (or you will need to
configure using option --without-x): X is part of the standard
OS X distribution in versions prior to Mountain Lion, but not always
installed. For Mountain Lion and later, see
https://xquartz.macosforge.org/. (Note that XQuartz will likely
need to be re-installed after an OS upgrade.)

The instructions here are for ‘x86_64’ builds on 10.6 (Snow
Leopard) or later. In principle R can be built for 10.4.x, 10.5.x
and for PowerPC or 32-bit Intel Macs but these has not been tested
recently.

To use the quartz() graphics device you need to configure with
--with-aqua (which is the default): quartz() then
becomes the default device when running R at the console and X11
would only be used for the command-line-R data editor/viewer and one
version of Tcl/Tk. (This needs an Objective-C compiler48 which can compile the source code of
quartz().)

Use --without-aqua if you want a standard Unix-alike build:
apart from disabling quartz() and the ability to use the build
with R.APP, it also changes the default location of the personal
library (see ?.libPaths()). Also use
--disable-R-framework to install in the standard layout.

Various compilers can be used. The current CRAN ‘Mavericks’
distribution of R is built using

Full names help to ensure that the intended compilers are used. In
particular gcc is a copy of llvm-gcc-4.2 for Xcode <
5 but of clang in Xcode 5. The recommended Fortran compiler
defaults to 32-bit, so -arch x86_64 is needed. (For a 32-bit
build, use -arch i386 for all compiler commands.)

The OpenMP support in this version of gcc is problematic, so
the CRAN build is configured with --disable-openmp.

Pre-compiled versions of many of the Useful libraries and programs
are available from http://r.research.att.com/libs/. You will
most likely want at least pcre, xz, jpeg,
libpng and readline (and perhaps tiff).
pkg-config is not provided by Apple and useful for many packages:
it will also be used if present when configuring the X11()
device.

Recent versions of OS X ship with zlib version 1.2.8 and
bzlib version 1.0.6, sufficient for the default
configure checks. Mavericks has a recent enough version of
libcurl: Snow Leopard does not.

The Accelerate library can be used via the configuration options

--with-blas="-framework Accelerate" --with-lapack

to provide potentially higher-performance versions of the BLAS
and LAPACK routines. (Use of Accelerate with
--with-lapack does not work on Snow Leopard: it may work there
without.)50

Looking at the top of
/Library/Frameworks/R.framework/Resources/etc/Makeconf
will show the compilers and configuration options used for the
CRAN binary package for R: at the time of writing

--enable-memory-profiling

was used for ‘Mavericks’.

Configure option --with-internal-tzcode is the default on OS X,
as a 64-bit time_t is available but the system implementation of
time zones does not work correctly for times before 1902 or after 2037.

The TeX implementation used by the developers is MacTeX
(https://www.tug.org/mactex/): the full installation is about 4GB,
but a smaller version is available at
https://www.tug.org/mactex/morepackages.html: you will need to add
some packages, e.g. for the 2015 version we needed to add
cm-super, helvetic, inconsolata and texinfo
which brought this to about 410MB (or package texinfo and the
collections collection-fontsrecommended,
collection-fontsextra and collection-latexextra which will
take this up to about 1GB). ‘TeX Live Utility’ (available
via the MacTeX front page) provides a graphical means to manage
TeX packages.

One OS X quirk is that the default path has /usr/local/bin after
/usr/bin, contrary to common practice on Unix-alikes. This means
that if you install tools from the sources they will by default be
installed under /usr/local and not supersede the system
versions.

C.3.1 Mavericks and later

For these versions Apple makes available compilers based on
clang, and C++ headers and runtime are from LLVM’s
‘libc++’ project, as part of the ‘Command Line Tools’ (sometimes
called ‘Command Line Developer Tools’).

These tools can be (re-)installed by xcode-select --install.
(If you have a fresh installation of Mavericks or latere, running e.g.
make in a terminal will offer the installation of the
command-line tools, or perhaps use the versions from Xcode. However,
after an OS update, you are advised to re-install them.)

To use the compilers from the command-line tools with the recommended
Fortran compiler, have in config.site something like

CC=clang
CXX=clang++
F77=gfortran-4.8
FC=$F77
OBJC=clang

(CC=gcc and CXX=g++ are slightly different front-ends to
the same compilers.) Recent versions of the CRAN binary package
installer for ‘Snow Leopard’ change the settings in etc/Makeconf
to

If you upgrade to Yosemite you should re-install any of XQuartz, the
‘Command Line Tools’ and Java which you have installed. (Upgrading may
partially remove previous versions which can be confusing.)

There are some problems with the recommended gfortran builds
under Yosemite. They give warnings and gfortran-4.8 is
reported to be unable to link packages containing Fortran 9x code. (The
solution is to use a compiler built under Yosemite.)

C.3.2 Lion and Mountain Lion

‘Command-line Tools for Xcode’ used to be part of the Apple Developer
Tools (‘Xcode’) but for these versions needs to be installed separately.
They can be downloaded from
http://developer.apple.com/devcenter/mac/ (you will need to
register there: that allows you to download older versions available for
your OS) or from within some versions of Xcode you can install the
command-line tools from the ‘Downloads’ pane in the
‘Preferences’.

The X11 system used with Mountain Lion is XQuartz (see above): Lion
included an X11 system.

To build the graphics devices depending on cairographics, the XQuartz
path for pkg-config files needs to be known to
pkg-config when configure is run: this usually means
adding it to the PKG_CONFIG_PATH environment variable, e.g.

C.3.3 Snow Leopard

A quirk on Snow Leopard is that the X11 libraries are not in the default
linking path, so something like ‘LIBS=-L/usr/X11/lib’ may be
required in config.site, or you can use the configure
options --x-includes=/usr/X11/include
--x-libraries=/usr/X11/lib .

The CRAN binaries are built using Xcode 4.2, a version
available only to subscribing developers. It is believed that 3.2.6 (the
last public free version for Snow Leopard) will work.

C.3.4 Tcl/Tk headers and libraries

If you plan to use the tcltk package for R, you need to
install a distribution of Tcl/Tk. There are two alternatives. If you
use R.APP you will want to use X11-based Tcl/Tk (as used on other
Unix-alikes), which is installed as part of the CRAN binary for R.
This may need

Note that this requires a fully-updated X11 installation (XQuartz for
Mountain Lion and later).

There is also a native (‘Aqua’) version of Tcl/Tk which produces widgets
in the native OS X style: this will not work with R.APP because of
conflicts over the OS X menu, but for those only using command-line R
this provides a much more intuitive interface to Tk for experienced Mac
users. Most versions of OS X come with Aqua Tcl/Tk libraries, but these
are not current (nor recent) versions of Tcl/Tk (8.5.9 in Mountain Lion
and Mavericks). It is better to install Tcl/Tk 8.6.x from the sources
or a binary distribution from
https://www.activestate.com/activetcl/downloads. Configure R
with

C.3.5 Java

The situation with Java support on OS X is messy, with Apple essentially
no longer supporting Java. Snow Leopard and Lion shipped with a Java 6
runtime (JRE).

Mountain Lion and later do not come with an installed JRE, and an OS X
upgrade removes one if already installed: it is intended to be installed
at first use. Check if a JRE is installed by running java
-version in a Terminal window: if Java is not installed this
should prompt you to install it.

You may need to install what Apple calls ‘legacy Java’51 to suppress pop-up
messages, at least under Yosemite, even if you have a current version
installed.

To see what compatible versions of Java are currently installed, run
/usr/libexec/java_home -V -a x86_64. If needed, set the
environment variable JAVA_HOME to choose between these, both when
R is built from the sources and when R CMD javareconf is
run.

Configuring and building R both looks for a JRE and for support for
compiling JNI programs (used by packages rJava and
JavaGD); the latter requires a JDK (Java SDK) and not just a
JRE.

The build process tries to fathom out what JRE/JDK to use, but it may
need some help, e.g. by setting JAVA_HOME. An Apple JRE can be
specified explicitly by something like

C.3.6 Frameworks

The CRAN build of R is installed as a framework, which is
selected by the default option

./configure --enable-R-framework

(This is intended to be used with an Apple toolchain: other compilers may
not support frameworks correctly.)

It is only needed if you want to build R for use with the R.APP
console, and implies --enable-R-shlib to build R as a
dynamic library. This option configures R to be built and installed
as a framework called R.framework. The default installation path
for R.framework is /Library/Frameworks but this can be
changed at configure time by specifying the flag
--enable-R-framework[=DIR] or at install time as

make prefix=/where/you/want/R.framework/to/go install

Note that installation as a framework is non-standard (especially to a
non-standard location) and utilities may not support it (e.g. the
pkg-config file libR.pc will be put somewhere unknown
to pkg-config).

C.3.7 Building R.app

Note that building the R.APP GUI console is a separate project, using
Xcode. Before compiling R.APP make sure the current version of R
is installed in /Library/Frameworks/R.framework and working at
the command-line (this can be a binary install).

The current sources can be checked out by

svn co https://svn.r-project.org/R-packages/trunk/Mac-GUI

This can be built by loading the R.xcodeproj project (select the
R target and a suitable configuration), or from the command-line
by e.g.

R.APP does not need to be installed in any specific way. Building
R.APP results in the R.APP bundle which appears as one R icon. This
application bundle can be run anywhere and it is customary to place it
in the /Applications folder.

C.4 Solaris

R has been built successfully on Solaris 10 (both Sparc and
‘x86’) using the (zero cost) Oracle Solaris Studio compilers:
there has been some success with
gcc 4/gfortran. (Recent Sun machines are AMD
Opterons or Intel Xeons (‘amd64’) rather than ‘x86’, but
32-bit ‘x86’ executables are the default.)

There have been few reports on Solaris 11, with no known extra issues.
Solaris 9 and earlier are now so old that it is unlikely that R is
still used with them, and they will not be considered here.

The Solaris versions of several of the tools needed to build R
(e.g. make, ar and ld) are in
/usr/ccs/bin, so if using those tools ensure this is in your
path. A version of the preferred GNUtar is (if
installed) in /usr/sfw/bin. It may be necessary to avoid the
tools in /usr/ucb: POSIX-compliant versions of some tools can be
found in /usr/xpg4/bin and /usr/xpg6/bin.

A large selection of Open Source software can be installed from
https://www.opencsw.org, by default installed under
/opt/csw. Solaris 10 ships with bzlib version 1.0.6
(sufficient for the default --with-system-bzlib) but
zlib version 1.2.3 (too old for --with-system-zlib):
OpenCSW has 1.2.8.

You will need GNUlibiconv and readline: the
Solaris version of iconv is not sufficiently powerful.

The native make suffices to build R but a small number of
packages require GNUmake (some without good reason
and without declaring it as ‘SystemRequirements’ in the
DESCRIPTION file).

Some people have reported that the Solaris libintl needs to be
avoided, for example by using --disable-nls or
--with-included-gettext or using libintl from OpenCSW.

The support for the C99 long double type on Sparc hardware uses
quad-precision arithmetic, and this is usually slow because it is done
by software emulation. On such systems configure option
--disable-long-double can be used for faster but less accurate
computations.

The Solaris time-zone conversion services seem to be unreliable pre-1916
in Europe (when daylight-savings time was first introduced): most often
reporting in the non-existent DST variant. Using configure
option --with-internal-tzcode is recommended, and required if
you find time-zone abbreviations being given odd values (as has been
seen on 64-bit builds without it).

When using the Oracle compilers52 do not specify -fast, as this
disables IEEE arithmetic and make check will fail.

It has been reported that some Solaris installations need

INTERNET_LIBS="-lsocket -lnsl"

on the configure command line or in file config.site;
however, there have been many successful installs without this.

A little juggling of paths was needed to ensure GNUlibiconv (in /usr/local) was used rather than the Solaris
iconv:

For a 64-bit target add -m64 to the compiler macros
and use something like LDFLAGS=-L/usr/local/lib/sparcv9 or
LDFLAGS=-L/usr/local/lib/amd64 as appropriate.
It will also be necessary to point pkg-config at the 64-bit
directories, e.g. one of

(and possibly other Fortran libraries, but this suffices for the
packages currently on CRAN).

Currently ‘amd64’ and ‘sparcv9’ builds work
out-of-the-box with Sun Studio 12u1 but not Solaris Studio 12.2 and
12.3: libRblas.so and lapack.so are generated with code
that causes relocation errors (which is being linked in from the Fortran
libraries). This means that building 64-bit R as a shared library
may be impossible with Solaris Studio >= 12.2. For a standard build the
trick seems to be to manually set FLIBS to avoid the troublesome
libraries. For example, on ‘amd64’ set in config.site
something like

but the use of -nofstore can be less numerically stable, and some
packages (notably mgcv on ‘x86’) failed to compile at
higher optimization levels with version 12.3.

The Solaris Studio compilers provide several implementations of the
C++98 standard which select both the set of headers and a C++ runtime
library. These are selected by the -library flag, which as it
is needed for both compiling and linking is best specified as part of
the compiler. The examples above use ‘stlport4’, currently the
most modern of the options: the default (but still needed to be
specified as it is needed for linking) is ‘Cstd’: see
http://developers.sun.com/solaris/articles/cmp_stlport_libCstd.html.
Note though that most external Solaris C++ libraries will have been
built with ‘Cstd’ and so an R package using such libraries also
needs to be. Occasionally the option -library=stlport4,Crun
has been needed.

Several CRAN packages using C++ need the more liberal
interpretation given by adding

CXXFLAGS="-features=tmplrefstatic"

The performance library sunperf is available for use with the
Solaris Studio compilers. If selected as a BLAS, it must also
be selected as LAPACK via (for Solaris Studio 12.2)

./configure --with-blas='-library=sunperf' --with-lapack

This has often given test failures in the past, in several different
places. At the time of writing it fails in tests/reg-BLAS.R, and on
some builds, including for ‘amd64’, it fails in
example(eigen).

Parsing very complex R expressions needs a lot of stack space when
the Oracle compilers are used: several packages require the stack
increased to at least 20MB.

C.4.1 Using gcc

If using gcc, ensure that the compiler was compiled for the
version of Solaris in use. (This can be ascertained from gcc
-v.) gcc makes modified versions of some header files, and
several reports of problems were due to using gcc compiled on
one version of Solaris on a later version.

The notes here are for gcc set up to use the Solaris linker:
it can also be set up to use GNU ld, but that has not been
tested.

C.5 AIX

We no longer support AIX prior to 4.2, and configure will
throw an error on such systems.

Ei-ji Nakama was able to build under AIX 5.2 on ‘powerpc’ with
GCC 4.0.3 in several configurations. 32-bit versions could be
configured with --without-iconv as well as
--enable-R-shlib. For 64-bit versions he used

On one AIX 6.x system it was necessary to use R_SHELL to set the
default shell to be Bash rather than Zsh.

Kurt Hornik and Stefan Theussl at WU (Wirtschaftsuniversität Wien)
successfully built R on a ‘powerpc’ (8-CPU Power6
system) running AIX 6.1, configuring with or without
--enable-R-shlib (Ei-ji Nakama’s support is gratefully
acknowledged).

It helps to describe the WU build environment first. A small part of
the software needed to build R and/or install packages is available
directly from the AIX Installation DVDs, e.g., Java 6 and X11.
Additional open source software (OSS) is packaged for AIX in .rpm
files and available from both IBM’s “AIX Toolbox for Linux
Applications”
(http://www-03.ibm.com/systems/power/software/aix/linux/) and
http://www.oss4aix.org/download/. The latter website typically
offers more recent versions of the available OSS. All tools needed and
libraries downloaded from these repositories (e.g., GCC, Make,
libreadline, etc.) are typically installed to
/opt/freeware, hence corresponding executables are found in
/opt/freeware/bin which thus needs to be in PATH for using
these tools. As on other Unix systems one needs GNUlibiconv as the AIX version of iconv is not sufficiently
powerful. Additionally, for proper Unicode compatibility one should
install the corresponding package from the ICU project
(http://www.icu-project.org/download/), which offers pre-compiled
binaries for various platforms which in case of AIX can be installed via
unpacking the tarball to the root file system. For full LaTeX
support one can install the TeX Live DVD distribution
(https://www.tug.org/texlive/): it is recommended to update the
distribution using the tlmgr update manager. For 64-bit R builds
supporting Tcl/Tk this needs to installed from the sources as available
pre-compiled binaries supply only 32-bit shared objects.

The recent WU testing was done using compilers from both the
GNU Compiler Collection (version 4.2.4) which is available
from one of the above OSS repositories, and the IBM C/C++ (XL C/C++
10.01) as well as FORTRAN (XL Fortran 12.01) compilers
(http://www14.software.ibm.com/webapp/download/byproduct.jsp#X).

for the IBM XL compilers. For the latter, it is important to note that
the decision for generating 32-bit or 64-bit code is done by setting the
OBJECT_MODE environment variable appropriately (recommended) or
using an additional compiler flag (-q32 or -q64). By
default the IBM XL compilers produce 32 bit code. Thus, to build R with
64-bit support one needs to either export OBJECT_MODE=64 in the
environment or, alternatively, use the -q64 compiler options.

It is strongly recommended to install Bash and use it as the configure
shell, e.g., via setting CONFIG_SHELL=/usr/bin/bash in the
environment, and to use GNU Make (e.g., via
(MAKE=/opt/freeware/bin/make).

C.6 FreeBSD

C.7 Cygwin

The Cygwin emulation layer on Windows can be treated as a Unix-alike OS.
This is unsupported, but experiments have been conducted and a few
workarounds added. Cygwin has not been tested for R 3.0.0 or later.

The 64-bit version is completely unsupported. The 32-bit version has
never worked well enough to pass R’s make check.

R requires C99 complex type support, which is available as from
Cygwin 1.7.8 (March 2011). However, the (then) implementation of
cacos gives incorrect results, so we undefine HAVE_CACOS
in src/main/complex.c on that platform. It has been reported
that some C99 long double mathematical functions are missing, so
configuring with --disable-long-double was required.

Enabling NLS does work if required, although adding
--with-included-gettext is preferable. You will see many
warnings about the use of auto-import. Setting ‘FLIBS’ explicitly
seems needed currently as the auto-detection gives an incorrect value.

You will need the tetex-extra Cygwin package to build
NEWS.pdf and the vignettes.

Note that this gives you a command-line application using readline
for command editing. The ‘X11’ graphics device will work if a
suitable X server is running, and the standard Unix-alike ways of
installing source packages work. There was a bug in the
/usr/lib/tkConfig.sh script in the version we looked at, which
needs to have

TK_LIB_SPEC='-ltk84'

The overhead of using shell scripts makes this noticeably slower than a
native build of R on Windows.

Even when R could be built, not all the tests passed: there were
incorrect results from wide-character regular expressions code and from
sourcing CR-delimited files.

Do not use Cygwin’s BLAS library: it is known to give incorrect results.

C.8 New platforms

There are a number of sources of problems when installing R on a new
hardware/OS platform. These include

Floating Point Arithmetic: R requires arithmetic compliant
with IEC 60559, also known as IEEE 754.
This mandates the use of plus and minus infinity and NaN (not a
number) as well as specific details of rounding. Although almost all
current FPUs can support this, selecting such support can be a pain.
The problem is that there is no agreement on how to set the signalling
behaviour; Sun/Sparc, SGI/IRIX and ‘ix86’ Linux require no
special action, FreeBSD requires a call to (the macro)
fpsetmask(0) and OSF1 required that computation be done with a
-ieee_with_inexact flag etc. On a new platform you must find
out the magic recipe and add some code to make it work. This can often
be done via the file config.site which resides in the top level
directory.

Beware of using high levels of optimization, at least initially. On
many compilers these reduce the degree of compliance to the
IEEE model. For example, using -fast on the Solaris
Studio compilers has caused R’s NaN to be set incorrectly, and
gcc’s -ffast-math and clang’s
-Ofast have given incorrect results.

Shared Objects: There seems to be very little agreement
across platforms on what needs to be done to build shared objects.
there are many different combinations of flags for the compilers and
loaders. GNU libtool cannot be used (yet), as it currently
does not fully support FORTRAN: one would need a shell wrapper for
this). The technique we use is to first interrogate the X window system
about what it does (using xmkmf), and then override this in
situations where we know better (for tools from the GNU
Compiler Collection and/or platforms we know about). This typically
works, but you may have to manually override the results. Scanning the
manual entries for cc and ld usually reveals the
correct incantation. Once you know the recipe you can modify the file
config.site (following the instructions therein) so that the
build will use these options.

It seems that gcc 3.4.x and later on ‘ix86’ Linux
defeat attempts by the LAPACK code to avoid computations entirely in
extended-precision registers, so file src/modules/lapack/dlamc.f
may need to be compiled without optimization. Set the configure
variable SAFE_FFLAGS to the flags to be used for this file. If
configure detects GNU FORTRAN it adds flag
-ffloat-store to FFLAGS. (Other settings are needed when
using icc on ‘ix86’ Linux, for example. Using
-mpc64 is preferable on more recent GCC compilers.)

If you do manage to get R running on a new platform please let us
know about it so we can modify the configuration procedures to include
that platform.

If you are having trouble getting R to work on your platform please
feel free to use the ‘R-devel’ mailing list to ask questions. We
have had a fair amount of practice at porting R to new platforms
...

Appendix D The Windows toolset

If you want to build R or add-on packages from source in Windows, you
will need to collect, install and test an extensive set of tools. See
https://CRAN.R-project.org/bin/windows/Rtools/ for the current
locations and other updates to these instructions. (Most Windows users
will not need to build add-on packages from source; see Add-on packages for details.)

We have found that the build process for R is quite sensitive to
the choice of tools: please follow our instructions exactly,
even to the choice of particular versions of the tools.54 The build process for add-on packages is somewhat more
forgiving, but we recommend using the exact toolset at first, and only
substituting other tools once you are familiar with the process.

This appendix contains a lot of prescriptive comments. They are
here as a result of bitter experience. Please do not report problems to
the R mailing lists unless you have followed all the prescriptions.

We have collected most of the necessary tools (unfortunately not all,
due to license or size limitations) into an executable installer
named55Rtools31.exe,
available from https://CRAN.R-project.org/bin/windows/Rtools/. You
should download and run it, choosing the default “Package authoring
installation” to build add-on packages, or the “full installation” if
you intend to build R.

You will need the following items to build R and packages.
See the subsections below for detailed descriptions.

The command line tools (in Rtools*.exe)

The MinGW-w64 32/64-bit toolchain to compile C, Fortran and C++.

For installing simple source packages containing data or R source but
no compiled code, none of these are needed.

A complete build of R including PDF manuals, and producing the
installer will also need the following:

LaTeX

The Inno Setup installer

(optional) qpdf

It is important to set your PATH properly. The installer
Rtools*.exe optionally sets the path to components that it
installs.

Your PATH may include . first, then the bin
directories of the tools, the compiler toolchain and LaTeX. Do not
use filepaths containing spaces: you can always use the short forms
(found by dir /x at the Windows command line). Network shares
(with paths starting \\) are not supported.

It is essential that the directory containing the command line tools
comes first or second in the path: there are typically like-named
tools56 in other directories, and they will not
work. The ordering of the other directories is less important, but if in
doubt, use the order above.

Our toolset contains copies of Cygwin DLLs that may conflict with other
ones on your system if both are in the path at once. The normal
recommendation is to delete the older ones; however, at one time we
found our tools did not work with a newer version of the Cygwin DLLs, so
it may be safest not to have any other version of the Cygwin DLLs in your
path.

D.1 LaTeX

The ‘MiKTeX’ (http://www.miktex.org/) distribution of
LaTeX includes a suitable port of pdftex. This can be set up
to install extra packages ‘on the fly’, which is the simplest way to use
it (and the default). The ‘basic’ version of ‘MiKTeX’ almost
suffices: when last tested packages

epsf fancyvrb inconsolata listings mptopdf natbib url

needed to be added (on the fly or via the ‘MiKTeX’ Package
Manager) to install R. In any case ensure that the inconsolata
package is installed—you can check with the ‘MiKTeX’ Package
Manager.

Please read Making the manuals about how to make fullrefman.pdf
and set the environment variable R_RD4PDF suitably; ensure you
have the required fonts installed or that ‘MiKTeX’ is set up to
install LaTeX packages on first use.

D.3 The command line tools

This item is installed by the Rtools*.exe installer.

If you choose to install these yourself, you will need suitable versions
of at least basename, cat, cmp, comm,
cp, cut, date, diff, du, echo,
expr, gzip, ls, make, makeinfo,
mkdir, mv, rm, rsync, sed, sh,
sort, tar, texindex, touch and uniq;
we use those from the Cygwin distribution
(https://www.cygwin.com/) or compiled from the sources. You will
also need zip and unzip from the Info-ZIP project
(http://www.info-zip.org/). All of these tools are in
Rtools*.exe.

Beware: ‘Native’ ports of make are not suitable
(including those called ‘MinGW make’ at the MinGW SourceForge site and
mingw32-make in some MinGW-w64 distributions). There were
also problems with other versions of the Cygwin tools and DLLs. To
avoid frustration, please use our tool set, and make sure it is at the
front of your path (including before the Windows system directories).
If you are using a Windows shell, type PATH at the prompt to find
out.

You may need to set the environment variable CYGWIN to a value
including ‘nodosfilewarning’ to suppress messages about
Windows-style paths.

D.4 The MinGW-w64 toolchain

Technically you need more than just a compiler so the set of tools is
referred to as a ‘toolchain’.

The preferred toolchain is part of Rtools31.exe: this uses a beta
version of gcc 4.6.3 and version 2.0.1 of the MinGW-w64
project’s runtime.

This toolchain uses multilib: that is there is a single front-end
such as gcc.exe for each of the compilers and 32-bit (the
default) and 64-bit compilation are selected by the flags57-m32 and -m64
respectively. The tools are all 32-bit Windows executables and should
be able to run on any current version of Windows—however you do need a
64-bit version of Windows to build 64-bit R as the build process runs
R.

To select a 32-bit or 64-bit build of R, set the options in
MkRules.local appropriately (following the comments in the file).

Some external software libraries will need to be re-compiled under the
new toolchain: especially those providing a C++ interface. Many of
those used by CRAN packages are available from
https://www.stats.ox.ac.uk/pub/Rtools/multilib/. Users
developing packages with Rcpp need to ensure that they use a
version built with exactly the same toolchain as their package: the
recommendation is to build Rcpp from its sources yourself.

There is support for OpenMP and pthreads in this toolchain. As the
performance of OpenMP on Windows is poor for small tasks, it is not used
for R itself.

D.5 Useful additional programs

The process of making the installer will make use of qpdf to
compact some of the package vignettes, if it is available. Windows
binaries of qpdf are available from
http://sourceforge.net/projects/qpdf/files/. Set the path
to the qpdf installation in file MkRules.local.

for a small number of
CRAN packages where this is known to be safe and is needed by
the autobuilder this is the default. Look at the source of
tools:::.install_packages for the list. It can also be specified
in the package’s DESCRIPTION file.

and not PCRE2, which started at version
10.0. PCRE must be built with UTF-8 support (not the default) and
support for Unicode properties is assumed by some R packages. Only
the first is tested by configure, but both can be checked at
run-time by calling pcre_config(). JIT support is desirable for
the best performance.